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ORCID38th NeurIPS 2024: Vancouver, BC, Canada
- Amir Globersons, Lester Mackey, Danielle Belgrave, Angela Fan, Ulrich Paquet, Jakub M. Tomczak, Cheng Zhang:
Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024. 2024 - Ionut-Vlad Modoranu, Mher Safaryan, Grigory Malinovsky, Eldar Kurtic, Thomas Robert, Peter Richtárik, Dan Alistarh:
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence. - Yanbin Wei, Shuai Fu, Weisen Jiang, Zejian Zhang, Zhixiong Zeng, Qi Wu, James T. Kwok, Yu Zhang:
GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning. - Changhoon Song, Yesom Park, Myungjoo Kang:
How does PDE order affect the convergence of PINNs? - Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lécué, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Fair Wasserstein Coresets. - Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang:
Improved Regret for Bandit Convex Optimization with Delayed Feedback. - Tomas Rigaux, Hisashi Kashima:
Enhancing Chess Reinforcement Learning with Graph Representation. - Ying Cheng, Yang Li, Junjie He, Rui Feng:
Mixtures of Experts for Audio-Visual Learning. - Markus Pettersen, Frederik Rogge, Mikkel E. Lepperød:
Learning Place Cell Representations and Context-Dependent Remapping. - Chih-Hung Liu, Gleb Novikov:
Robust Sparse Regression with Non-Isotropic Designs. - Hancheng Ye, Jiakang Yuan, Renqiu Xia, Xiangchao Yan, Tao Chen, Junchi Yan, Botian Shi, Bo Zhang:
Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy. - Xuan Zhang, Chao Du, Tianyu Pang, Qian Liu, Wei Gao, Min Lin:
Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs. - Shangzi Xue, Zhenya Huang, Jiayu Liu, Xin Lin, Yuting Ning, Binbin Jin, Xin Li, Qi Liu:
Decompose, Analyze and Rethink: Solving Intricate Problems with Human-like Reasoning Cycle. - Jiesong Liu, Feng Zhang, Jiawei Guan, Xipeng Shen:
UQ-Guided Hyperparameter Optimization for Iterative Learners. - Audrey Huang, Nan Jiang:
Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality. - Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Guo Qin, Haoran Zhang, Yong Liu, Yunzhong Qiu, Jianmin Wang, Mingsheng Long:
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables. - Mohamed Elrefaie, Florin Morar, Angela Dai, Faez Ahmed:
DrivAerNet++: A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks. - Yuxuan Duan, Yan Hong, Bo Zhang, Jun Lan, Huijia Zhu, Weiqiang Wang, Jianfu Zhang, Li Niu, Liqing Zhang:
DomainGallery: Few-shot Domain-driven Image Generation by Attribute-centric Finetuning. - Weibo Gao, Qi Liu, Linan Yue, Fangzhou Yao, Hao Wang, Yin Gu, Zheng Zhang:
Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling. - Minghao Chen, Yihang Li, Yanting Yang, Shiyu Yu, Binbin Lin, Xiaofei He:
AutoManual: Constructing Instruction Manuals by LLM Agents via Interactive Environmental Learning. - Jiaqi Xu, Cuiling Lan, Wenxuan Xie, Xuejin Chen, Yan Lu:
Slot-VLM: Object-Event Slots for Video-Language Modeling. - Sicheng Xu, Guojun Chen, Yu-Xiao Guo, Jiaolong Yang, Chong Li, Zhenyu Zang, Yizhong Zhang, Xin Tong, Baining Guo:
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time. - Andrew Davison, S. Carlyle Morgan, Owen G. Ward:
Community Detection Guarantees using Embeddings Learned by Node2Vec. - Zijie Huang, Wanjia Zhao, Jingdong Gao, Ziniu Hu, Xiao Luo, Yadi Cao, Yuanzhou Chen, Yizhou Sun, Wei Wang:
Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling. - Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Tom Lieberum, Vikrant Varma, János Kramár, Rohin Shah, Neel Nanda:
Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders. - Xiaosong Jia, Zhenjie Yang, Qifeng Li, Zhiyuan Zhang, Junchi Yan:
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving. - Gautham Vasan, Mohamed Elsayed, Seyed Alireza Azimi, Jiamin He, Fahim Shahriar, Colin Bellinger, Martha White, Rupam Mahmood:
Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers. - Ruifeng Ren, Yong Liu:
Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens. - Nicholas Babaev, Kirill Tamogashev, Azat Saginbaev, Ivan Shchekotov, Hanbin Bae, Hosang Sung, Won-Jun Lee, Hoon-Young Cho, Pavel Andreev:
FINALLY: fast and universal speech enhancement with studio-like quality. - Can Jin, Tong Che, Hongwu Peng, Yiyuan Li, Dimitris N. Metaxas, Marco Pavone:
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate. - Wuxuan Shi, Mang Ye:
Prospective Representation Learning for Non-Exemplar Class-Incremental Learning. - Matthew Macfarlane, Edan Toledo, Donal Byrne, Paul Duckworth, Alexandre Laterre:
SPO: Sequential Monte Carlo Policy Optimisation. - Jin Woo Lee, Jaehyun Park, Min Jun Choi, Kyogu Lee:
Differentiable Modal Synthesis for Physical Modeling of Planar String Sound and Motion Simulation. - Jiaqi Wang, Xiaochen Wang, Lingjuan Lyu, Jinghui Chen, Fenglong Ma:
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection. - Yu Zhang, Changhao Pan, Wenxiang Guo, Ruiqi Li, Zhiyuan Zhu, Jialei Wang, Wenhao Xu, Jingyu Lu, Zhiqing Hong, Chuxin Wang, Lichao Zhang, Jinzheng He, Ziyue Jiang, Yuxin Chen, Chen Yang, Jiecheng Zhou, Xinyu Cheng, Zhou Zhao:
GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks. - Yifan Li, Yikai Wang, Yanwei Fu, Dongyu Ru, Zheng Zhang, Tong He:
Unified Lexical Representation for Interpretable Visual-Language Alignment. - Andrea Amaduzzi, Pierluigi Zama Ramirez, Giuseppe Lisanti, Samuele Salti, Luigi Di Stefano:
LLaNA: Large Language and NeRF Assistant. - Zhihang Yuan, Hanling Zhang, Lu Pu, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang:
DiTFastAttn: Attention Compression for Diffusion Transformer Models. - Vincent Hanke, Tom Blanchard, Franziska Boenisch, Iyiola E. Olatunji, Michael Backes, Adam Dziedzic:
Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives. - Kseniya Cherenkova, Elona Dupont, Anis Kacem, Gleb Gusev, Djamila Aouada:
SpelsNet: Surface Primitive Elements Segmentation by B-Rep Graph Structure Supervision. - Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, Michael W. Mahoney, Yakun Sophia Shao, Kurt Keutzer, Amir Gholami:
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization. - Weicai Ye, Chenhao Ji, Zheng Chen, Junyao Gao, Xiaoshui Huang, Song-Hai Zhang, Wanli Ouyang, Tong He, Cairong Zhao, Guofeng Zhang:
DiffPano: Scalable and Consistent Text to Panorama Generation with Spherical Epipolar-Aware Diffusion. - Mouad El Bouchattaoui, Myriam Tami, Benoit Lepetit, Paul-Henry Cournède:
Causal Contrastive Learning for Counterfactual Regression Over Time. - Weizhi Gao, Zhichao Hou, Han Xu, Xiaorui Liu:
Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing. - Sergio Hernan Garrido Mejia, Patrick Blöbaum, Bernhard Schölkopf, Dominik Janzing:
Causal vs. Anticausal merging of predictors. - Yanzhi Li, Keqiu Li, Li Guohui, Zumin Wang, Changqing Ji, Lubo Wang, Die Zuo, Qing Guo, Feng Zhang, Manyu Wang, Di Lin:
Sim2Real-Fire: A Multi-modal Simulation Dataset for Forecast and Backtracking of Real-world Forest Fire. - Dan Zhang, Ziniu Hu, Sining Zhoubian, Zhengxiao Du, Kaiyu Yang, Zihan Wang, Yisong Yue, Yuxiao Dong, Jie Tang:
SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models. - Zhilin Wang, Yi Dong, Olivier Delalleau, Jiaqi Zeng, Gerald Shen, Daniel Egert, Jimmy Zhang, Makesh Narsimhan Sreedhar, Oleksii Kuchaiev:
HelpSteer 2: Open-source dataset for training top-performing reward models. - Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn:
Efficient Adversarial Training in LLMs with Continuous Attacks. - Zhu Yu, Runmin Zhang, Jiacheng Ying, Junchen Yu, Xiaohai Hu, Lun Luo, Si-Yuan Cao, Hui-Liang Shen:
Context and Geometry Aware Voxel Transformer for Semantic Scene Completion. - Quentin Leboutet, Nina Wiedemann, Zhipeng Cai, Michael Paulitsch, Kai Yuan:
MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs. - Samuel Teuber, Stefan Mitsch, André Platzer:
Provably Safe Neural Network Controllers via Differential Dynamic Logic. - Jason Hu, Bowen Song, Xiaojian Xu, Liyue Shen, Jeffrey A. Fessler:
Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems. - Yangru Huang, Peixi Peng, Yifan Zhao, Guangyao Chen, Yonghong Tian:
Seek Commonality but Preserve Differences: Dissected Dynamics Modeling for Multi-modal Visual RL. - Julian Rodemann, Christoph Jansen, Georg Schollmeyer:
Reciprocal Learning. - Yikun Jiang, Huanyu Wang, Lei Xie, Hanbin Zhao, Zhang Chao, Hui Qian, John C. S. Lui:
D-LLM: A Token Adaptive Computing Resource Allocation Strategy for Large Language Models. - Pierre Clavier, Laixi Shi, Erwan Le Pennec, Eric Mazumdar, Adam Wierman, Matthieu Geist:
Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms. - Jun Xia, Shaorong Chen, Jingbo Zhou, Xiaojun Shan, Wenjie Du, Zhangyang Gao, Cheng Tan, Bozhen Hu, Jiangbin Zheng, Stan Z. Li:
AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases. - Zhenhui Ye, Tianyun Zhong, Yi Ren, Ziyue Jiang, Jiawei Huang, Rongjie Huang, Jinglin Liu, Jinzheng He, Chen Zhang, Zehan Wang, Xize Cheng, Xiang Yin, Zhou Zhao:
MimicTalk: Mimicking a personalized and expressive 3D talking face in minutes. - Kun Zhou, Beichen Zhang, Jiapeng Wang, Zhipeng Chen, Xin Zhao, Jing Sha, Zhichao Sheng, Shijin Wang, Ji-Rong Wen:
JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models. - Kun Yan, Zeyu Wang, Lei Ji, Yuntao Wang, Nan Duan, Shuai Ma:
Voila-A: Aligning Vision-Language Models with User's Gaze Attention. - Linus Ericsson, Miguel Espinosa, Chenhongyi Yang, Antreas Antoniou, Amos J. Storkey, Shay B. Cohen, Steven McDonagh, Elliot J. Crowley:
einspace: Searching for Neural Architectures from Fundamental Operations. - Julia Costacurta, Shaunak Bhandarkar, David M. Zoltowski, Scott W. Linderman:
Structured flexibility in recurrent neural networks via neuromodulation. - Felipe Garrido-Lucero, Benjamin Heymann, Maxime Vono, Patrick Loiseau, Vianney Perchet:
DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation. - Xingyu Zhu, Beier Zhu, Yi Tan, Shuo Wang, Yanbin Hao, Hanwang Zhang:
Enhancing Zero-Shot Vision Models by Label-Free Prompt Distribution Learning and Bias Correcting. - Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Yifan Chen, Han Zhao, Qingfu Zhang:
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch. - Shaurya Dewan, Rushikesh Zawar, Prakanshul Saxena, Yingshan Chang, Andrew Luo, Yonatan Bisk:
Diffusion PID: Interpreting Diffusion via Partial Information Decomposition. - Bing Cao, Yinan Xia, Yi Ding, Changqing Zhang, Qinghua Hu:
Test-Time Dynamic Image Fusion. - Huilong Jin, Yingxue Zhang, Lei Shi, Shuang Zhang, Feifei Kou, Jiapeng Yang, Chuangying Zhu, Jia Luo:
An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval. - Haoye Dong, Aviral Chharia, Wenbo Gou, Francisco Vicente Carrasco, Fernando De la Torre:
Hamba: Single-view 3D Hand Reconstruction with Graph-guided Bi-Scanning Mamba. - Zhengyi Luo, Jinkun Cao, Sammy Christen, Alexander Winkler, Kris Kitani, Weipeng Xu:
Omnigrasp: Grasping Diverse Objects with Simulated Humanoids. - Zifan Song, Yudong Wang, Wenwei Zhang, Kuikun Liu, Chengqi Lyu, Demin Song, Qipeng Guo, Hang Yan, Dahua Lin, Kai Chen, Cairong Zhao:
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data. - Xiaoyuan Zhang, Genghui Li, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang:
Gliding over the Pareto Front with Uniform Designs. - Manuel Meier, Berken Utku Demirel, Christian Holz:
WildPPG: A Real-World PPG Dataset of Long Continuous Recordings. - Wanhua Li, Zibin Meng, Jiawei Zhou, Donglai Wei, Chuang Gan, Hanspeter Pfister:
SocialGPT: Prompting LLMs for Social Relation Reasoning via Greedy Segment Optimization. - Recep Yusuf Bekci:
Online Learning of Delayed Choices. - Jeremias Traub, Till J. Bungert, Carsten T. Lüth, Michael Baumgartner, Klaus H. Maier-Hein, Lena Maier-Hein, Paul F. Jaeger:
Overcoming Common Flaws in the Evaluation of Selective Classification Systems. - Shentong Mo, Peter Tong:
Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning. - Anqi Mao, Mehryar Mohri, Yutao Zhong:
Multi-Label Learning with Stronger Consistency Guarantees. - Xinyi Xu, Shuaiqi Wang, Chuan Sheng Foo, Bryan Kian Hsiang Low, Giulia Fanti:
Data Distribution Valuation. - Zander W. Blasingame, Chen Liu:
AdjointDEIS: Efficient Gradients for Diffusion Models. - Connor Brennan, Andrew Williams, Omar G. Younis, Vedant Vyas, Daria Yasafova, Irina Rish:
Using Unity to Help Solve Reinforcement Learning. - Or Sheffet, Daniel Omer:
Differentially Private Equivalence Testing for Continuous Distributions and Applications. - Haozhe Tian, Homayoun Hamedmoghadam, Robert Shorten, Pietro Ferraro:
Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systems. - David Samuel:
BERTs are Generative In-Context Learners. - Jiahe Bai, Baojian Zhou, Deqing Yang, Yanghua Xiao:
Faster Local Solvers for Graph Diffusion Equations. - Dailing Zhang, Shiyu Hu, Xiaokun Feng, Xuchen Li, Meiqi Wu, Jing Zhang, Kaiqi Huang:
Beyond Accuracy: Tracking more like Human via Visual Search. - Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju:
Credit Attribution and Stable Compression. - Junyang Wang, Haiyang Xu, Haitao Jia, Xi Zhang, Ming Yan, Weizhou Shen, Ji Zhang, Fei Huang, Jitao Sang:
Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration. - Mohammad Mahmudul Alam, Alexander Oberle, Edward Raff, Stella Biderman, Tim Oates, James Holt:
A Walsh Hadamard Derived Linear Vector Symbolic Architecture. - Wei Liu, Chenxi Wang, Yifei Wang, Zihao Xie, Rennai Qiu, Yufan Dang, Zhuoyun Du, Weize Chen, Cheng Yang, Chen Qian:
Autonomous Agents for Collaborative Task under Information Asymmetry. - Jingwei Liu, Ling Yang, Hongyan Li, Shenda Hong:
Retrieval-Augmented Diffusion Models for Time Series Forecasting. - Hadi Hosseini, Debmalya Mandal, Amrit Puhan:
The Surprising Effectiveness of SP Voting with Partial Preferences. - Qijian Zhang, Junhui Hou, Wenping Wang, Ying He:
Flatten Anything: Unsupervised Neural Surface Parameterization. - Lin Gui, Cristina Garbacea, Victor Veitch:
BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling. - Hyunseok Lee, Jihoon Tack, Jinwoo Shin:
ReMoDetect: Reward Models Recognize Aligned LLM's Generations. - Atli Kosson, Bettina Messmer, Martin Jaggi:
Analyzing & Reducing the Need for Learning Rate Warmup in GPT Training. - Niki Maria Foteinopoulou, Enjie Ghorbel, Djamila Aouada:
A Hitchhiker's Guide to Fine-Grained Face Forgery Detection Using Common Sense Reasoning. - Siyuan Xu, Minghui Zhu:
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator. - Ivan Butakov, Aleksander Tolmachev, Sofia Malanchuk, Anna Neopryatnaya, Alexey A. Frolov:
Mutual Information Estimation via Normalizing Flows. - Haozhe Zhao, Xiaojian (Shawn) Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, Baobao Chang:
UltraEdit: Instruction-based Fine-Grained Image Editing at Scale. - Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Animashree Anandkumar, Frances H. Arnold, Yisong Yue:
CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes. - Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu:
Few-Shot Adversarial Prompt Learning on Vision-Language Models. - Fangjinhua Wang, Marie-Julie Rakotosaona, Michael Niemeyer, Richard Szeliski, Marc Pollefeys, Federico Tombari:
UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections. - Huzi Cheng, Joshua W. Brown:
Goal Reduction with Loop-Removal Accelerates RL and Models Human Brain Activity in Goal-Directed Learning. - Adrian Bulat, Yassine Ouali, Georgios Tzimiropoulos:
QBB: Quantization with Binary Bases for LLMs. - Xiang Li, Jian Ding, Mohamed Elhoseiny:
VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding. - Naoki Hiratani:
Disentangling and mitigating the impact of task similarity for continual learning. - Asaf Cassel, Aviv Rosenberg:
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes. - Tianyi Zhang, Jonah Yi, Zhaozhuo Xu, Anshumali Shrivastava:
KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization. - Qiannan Zhang, Weishen Pan, Zilong Bai, Chang Su, Fei Wang:
Unified Insights: Harnessing Multi-modal Data for Phenotype Imputation via View Decoupling. - Lasse Vuursteen:
Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime. - Chengzhengxu Li, Xiaoming Liu, Zhaohan Zhang, Yichen Wang, Chen Liu, Yu Lan, Chao Shen:
Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models. - Chao Chen, Chenghua Guo, Rufeng Chen, Guixiang Ma, Ming Zeng, Xiangwen Liao, Xi Zhang, Sihong Xie:
Training for Stable Explanation for Free. - Bernardo Esteves, Miguel Vasco, Francisco S. Melo:
NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks. - Ruohan Li, Yiqun Xie, Xiaowei Jia, Dongdong Wang, Yanhua Li, Yingxue Zhang, Zhihao Wang, Zhili Li:
SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-situ Observations for Large-scale Solar Energy Forecasting. - Junyu Liu, Xiangjun Peng:
Feint Behaviors and Strategies: Formalization, Implementation and Evaluation. - Yixiao Xu, Binxing Fang, Mohan Li, Keke Tang, Zhihong Tian:
LT-Defense: Searching-free Backdoor Defense via Exploiting the Long-tailed Effect. - Yang Yang, Wendi Ren, Shuang Li:
HyperLogic: Enhancing Diversity and Accuracy in Rule Learning with HyperNets. - Zhongzhen Huang, Yankai Jiang, Rongzhao Zhang, Shaoting Zhang, Xiaofan Zhang:
CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation. - Jamie Lohoff, Emre Neftci:
Optimizing Automatic Differentiation with Deep Reinforcement Learning. - Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof:
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. - Eric Balkanski, Will Ma, Andreas Maggiori:
Fair Secretaries with Unfair Predictions. - Alexander Tyurin, Marta Pozzi, Ivan Ilin, Peter Richtárik:
Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity. - Lucas Slot, Stefan Tiegel, Manuel Wiedmer:
Testably Learning Polynomial Threshold Functions. - Lakshmi Narasimhan Govindarajan, Abhiram Iyer, Valmiki Kothare, Ila Fiete:
Flexible Context-Driven Sensory Processing in Dynamical Vision Models. - Andres Potapczynski, Shikai Qiu, Marc Finzi, Christopher Ferri, Charlie Chen, Micah Goldblum, C. Bayan Bruss, Christopher De Sa, Andrew Gordon Wilson:
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices. - Jiamian Wang, Pichao Wang, Dongfang Liu, Qiang Guan, Sohail A. Dianat, Majid Rabbani, Raghuveer Rao, Zhiqiang Tao:
Diffusion-Inspired Truncated Sampler for Text-Video Retrieval. - Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley, Otmar Hilliges, Romann M. Weber:
LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models. - Huayang Huang, Yu Wu, Qian Wang:
ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization. - Nikhil Behari, Edwin Zhang, Yunfan Zhao, Aparna Taneja, Dheeraj Nagaraj, Milind Tambe:
A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health. - Jitao Zhao, Di Jin, Meng Ge, Lianze Shan, Xin Wang, Dongxiao He, Zhiyong Feng:
FUG: Feature-Universal Graph Contrastive Pre-training for Graphs with Diverse Node Features. - Yiqun Mei, Jiacong Xu, Vishal M. Patel:
ReGS: Reference-based Controllable Scene Stylization with Gaussian Splatting. - Atharva Mete, Haotian Xue, Albert Wilcox, Yongxin Chen, Animesh Garg:
QueST: Self-Supervised Skill Abstractions for Learning Continuous Control. - Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu:
DiffPhyCon: A Generative Approach to Control Complex Physical Systems. - Wenliang Zhao, Minglei Shi, Xumin Yu, Jie Zhou, Jiwen Lu:
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner. - Zhengbang Zhu, Minghuan Liu, Liyuan Mao, Bingyi Kang, Minkai Xu, Yong Yu, Stefano Ermon, Weinan Zhang:
MADiff: Offline Multi-agent Learning with Diffusion Models. - Gabriele Farina, Charilaos Pipis:
Polynomial-Time Computation of Exact $\Phi$-Equilibria in Polyhedral Games. - Sheng-Yu Wang, Aaron Hertzmann, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang:
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images. - Xi Yu, Shinjae Yoo, Yuewei Lin:
CLIPCEIL: Domain Generalization through CLIP via Channel rEfinement and Image-text aLignment. - Linus Jeary, Tom Kuipers, Mehran Hosseini, Nicola Paoletti:
Verifiably Robust Conformal Prediction. - Zhuopeng Xu, Yujie Li, Cheng Liu, Ning Gui:
Ordering-Based Causal Discovery for Linear and Nonlinear Relations. - Longfei Ma, Yiyou Sun, Kaize Ding, Zemin Liu, Fei Wu:
Revisiting Score Propagation in Graph Out-of-Distribution Detection. - Ian Covert, Chanwoo Kim, Su-In Lee, James Y. Zou, Tatsunori B. Hashimoto:
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution. - Haocheng Luo, Tuan Truong, Tung Pham, Mehrtash Harandi, Dinh Q. Phung, Trung Le:
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization. - Ruikai Cui, Xibin Song, Weixuan Sun, Senbo Wang, Weizhe Liu, Shenzhou Chen, Taizhang Shang, Yang Li, Nick Barnes, Hongdong Li, Pan Ji:
LAM3D: Large Image-Point Clouds Alignment Model for 3D Reconstruction from Single Image. - Seijin Kobayashi, Yassir Akram, Johannes von Oswald:
Weight decay induces low-rank attention layers. - Lingxiang Jia, Yuchen Ying, Zunlei Feng, Zipeng Zhong, Shaolun Yao, Jiacong Hu, Mingjiang Duan, Xingen Wang, Jie Song, Mingli Song:
Association Pattern-aware Fusion for Biological Entity Relationship Prediction. - Yongliang Shen, Kaitao Song, Xu Tan, Wenqi Zhang, Kan Ren, Siyu Yuan, Weiming Lu, Dongsheng Li, Yueting Zhuang:
TaskBench: Benchmarking Large Language Models for Task Automation. - Hang Zhou, Yehui Tang, Haochen Qin, Yujie Yang, Renren Jin, Deyi Xiong, Kai Han, Yunhe Wang:
Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning. - Boyao Li, Alexander Thomson, Houssam Nassif, Matthew Engelhard, David Page:
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. - Benedikt Böck, Sadaf Syed, Wolfgang Utschick:
Sparse Bayesian Generative Modeling for Compressive Sensing. - Hezhe Qiao, Qingsong Wen, Xiaoli Li, Ee-Peng Lim, Guansong Pang:
Generative Semi-supervised Graph Anomaly Detection. - Xiuying Wei, Skander Moalla, Razvan Pascanu, Caglar Gulcehre:
Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers. - Shihong Ding, Long Yang, Luo Luo, Cong Fang:
Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition. - Rayna Andreeva, Benjamin Dupuis, Rik Sarkar, Tolga Birdal, Umut Simsekli:
Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms. - Zhanhui Zhou, Zhixuan Liu, Jie Liu, Zhichen Dong, Chao Yang, Yu Qiao:
Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models. - Binghui Xie, Yixuan Wang, Yongqiang Chen, Kaiwen Zhou, Yu Li, Wei Meng, James Cheng:
HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection. - Shivam Grover, Amin Jalali, Ali Etemad:
Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations. - Youcheng Zhang, Liwen Zhang, ZijunHu, Pengcheng Pi, Teng Li, Yuanpei Chen, Shi Peng, Zhe Ma:
TARSS-Net: Temporal-Aware Radar Semantic Segmentation Network. - Junkun Chen, Yu-Xiong Wang:
ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing. - Laurent Mertens, Elahe Yargholi, Hans P. Op de Beeck, Jan Van den Stock, Joost Vennekens:
FindingEmo: An Image Dataset for Emotion Recognition in the Wild. - Dan Shi, Renren Jin, Tianhao Shen, Weilong Dong, Xinwei Wu, Deyi Xiong:
IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons. - Zhuoyan Li, Ming Yin:
Utilizing Human Behavior Modeling to Manipulate Explanations in AI-Assisted Decision Making: The Good, the Bad, and the Scary. - Yu Zeng, Yang Zhang, Jiachen Liu, Linlin Shen, Kaijun Deng, Weizhao He, Jinbao Wang:
HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion. - Vladimir Malinovskii, Denis Mazur, Ivan Ilin, Denis Kuznedelev, Konstantin Burlachenko, Kai Yi, Dan Alistarh, Peter Richtárik:
PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression. - Klara Kaleb, Barbara Feulner, Juan Gallego, Claudia Clopath:
Feedback control guides credit assignment in recurrent neural networks. - Abhinav Joshi, Areeb Ahmad, Ashutosh Modi:
COLD: Causal reasOning in cLosed Daily activities. - Jianyi Zhang, Da-Cheng Juan, Cyrus Rashtchian, Chun-Sung Ferng, Heinrich Jiang, Yiran Chen:
SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models. - Jiongxiao Wang, Jiazhao Li, Yiquan Li, Xiangyu Qi, Junjie Hu, Sharon Li, Patrick McDaniel, Muhao Chen, Bo Li, Chaowei Xiao:
BackdoorAlign: Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment. - Peiyuan Feng, Yichen He, Guanhua Huang, Yuan Lin, Hanchong Zhang, Yuchen Zhang, Hang Li:
AGILE: A Novel Reinforcement Learning Framework of LLM Agents. - Hang Yin, Xiuwei Xu, Zhenyu Wu, Jie Zhou, Jiwen Lu:
SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation. - Reuben Adams, John Shawe-Taylor, Benjamin Guedj:
Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound. - Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li:
Can Graph Learning Improve Planning in LLM-based Agents? - Junoh Lee, Changyeon Won, Hyunjun Jung, Inhwan Bae, Hae-Gon Jeon:
Fully Explicit Dynamic Gaussian Splatting. - Timon Barlag, Vivian Holzapfel, Laura Strieker, Jonni Virtema, Heribert Vollmer:
Graph Neural Networks and Arithmetic Circuits. - Nikil Roashan Selvam, Amil Merchant, Stefano Ermon:
Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations. - Alexander David Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob N. Foerster:
Can Learned Optimization Make Reinforcement Learning Less Difficult? - Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind:
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling. - Qingqi Zhang, Ruize Xu, Risi Kondor:
Schur Nets: exploiting local structure for equivariance in higher order graph neural networks. - Runjia Zeng, Cheng Han, Qifan Wang, Chunshu Wu, Tong Geng, Lifu Huang, Ying Nian Wu, Dongfang Liu:
Visual Fourier Prompt Tuning. - Benjamin Rozonoyer, Michael Boratko, Dhruvesh Patel, Wenlong Zhao, Shib Sankar Dasgupta, Hung Le, Andrew McCallum:
Learning Representations for Hierarchies with Minimal Support. - Chester Holtz, Pengwen Chen, Zhengchao Wan, Chung-Kuan Cheng, Gal Mishne:
Continuous Partitioning for Graph-Based Semi-Supervised Learning. - Hezhen Hu, Zhiwen Fan, Tianhao Wu, Yihan Xi, Seoyoung Lee, Georgios Pavlakos, Zhangyang Wang:
Expressive Gaussian Human Avatars from Monocular RGB Video. - Bobak T. Kiani, Jason Wang, Melanie Weber:
Hardness of Learning Neural Networks under the Manifold Hypothesis. - Wei Li, Hehe Fan, Yongkang Wong, Mohan S. Kankanhalli, Yi Yang:
TOPA: Extending Large Language Models for Video Understanding via Text-Only Pre-Alignment. - Yibo Wang, Jun-Yi Hang, Min-Ling Zhang:
Multi-Label Open Set Recognition. - Keying Kuang, Frances Dean, Jack B. Jedlicki, David Ouyang, Anthony Philippakis, David A. Sontag, Ahmed M. Alaa:
Med-Real2Sim: Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning. - Feng Lu, Xinyao Zhang, Canming Ye, Shuting Dong, Lijun Zhang, Xiangyuan Lan, Chun Yuan:
SuperVLAD: Compact and Robust Image Descriptors for Visual Place Recognition. - Xavier Gonzalez, Andrew Warrington, Jimmy T. H. Smith, Scott W. Linderman:
Towards Scalable and Stable Parallelization of Nonlinear RNNs. - Zhifan Ye, Chenxi Wan, Chaojian Li, Jihoon Hong, Sixu Li, Leshu Li, Yongan Zhang, Yingyan (Celine) Lin:
3D Gaussian Rendering Can Be Sparser: Efficient Rendering via Learned Fragment Pruning. - Alexander Soen, Ke Sun:
Trade-Offs of Diagonal Fisher Information Matrix Estimators. - Yue Liu, Shihao Zhu, Jun Xia, Yingwei Ma, Jian Ma, Xinwang Liu, Shengju Yu, Kejun Zhang, Wenliang Zhong:
End-to-end Learnable Clustering for Intent Learning in Recommendation. - Duo Wang, Yuan Zuo, Fengzhi Li, Junjie Wu:
LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings. - Yooju Shin, Jaehyun Park, Susik Yoon, Hwanjun Song, Byung Suk Lee, Jae-Gil Lee:
Exploiting Representation Curvature for Boundary Detection in Time Series. - Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier De Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin:
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks. - Qinggang Zhang, Junnan Dong, Hao Chen, Daochen Zha, Zailiang Yu, Xiao Huang:
KnowGPT: Knowledge Graph based Prompting for Large Language Models. - Zhi Zheng, Changliang Zhou, Xialiang Tong, Mingxuan Yuan, Zhenkun Wang:
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems. - Chong Ma, Hanqi Jiang, Wenting Chen, Yiwei Li, Zihao Wu, Xiaowei Yu, Zhengliang Liu, Lei Guo, Dajiang Zhu, Tuo Zhang, Dinggang Shen, Tianming Liu, Xiang Li:
Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning. - Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai:
Federated Ensemble-Directed Offline Reinforcement Learning. - Ji-An Li, Corey Y. Zhou, Marcus K. Benna, Marcelo G. Mattar:
Linking In-context Learning in Transformers to Human Episodic Memory. - Wuyang Chen, Jialin Song, Pu Ren, Shashank Subramanian, Dmitriy Morozov, Michael W. Mahoney:
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning. - Fei Shen, Jinhui Tang:
IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation. - Albert Gong, Kyuseong Choi, Raaz Dwivedi:
Supervised Kernel Thinning. - Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao, Boyu Han, Yue Li, Jian Tang:
Cell ontology guided transcriptome foundation model. - Mixue Xie, Shuang Li, Binhui Xie, Chi Harold Liu, Jian Liang, Zixun Sun, Ke Feng, Chengwei Zhu:
Weight Diffusion for Future: Learn to Generalize in Non-Stationary Environments. - Viet Ho Tam Thuc Do, Parham Eftekhar, Seyed Alireza Hosseini, Gene Cheung, Philip A. Chou:
Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors. - Mayank Shrivastava, Berivan Isik, Qiaobo Li, Sanmi Koyejo, Arindam Banerjee:
Sketching for Distributed Deep Learning: A Sharper Analysis. - Yonghan Jung, Jin Tian, Elias Bareinboim:
Unified Covariate Adjustment for Causal Inference. - Elizabeth Collins-Woodfin, Inbar Seroussi, Begoña García Malaxechebarría, Andrew W. Mackenzie, Elliot Paquette, Courtney Paquette:
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms. - Biqing Qi, Yiang Luo, Junqi Gao, Pengfei Li, Kai Tian, Zhiyuan Ma, Bowen Zhou:
Exploring Adversarial Robustness of Deep State Space Models. - Joseph Ortiz, Antoine Dedieu, Wolfgang Lehrach, J. Swaroop Guntupalli, Carter Wendelken, Ahmad Humayun, Sivaramakrishnan Swaminathan, Guangyao Zhou, Miguel Lázaro-Gredilla, Kevin P. Murphy:
DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors. - Haoyu Dong, Huiqiao Fu, Wentao Xu, Zhehao Zhou, Chunlin Chen:
EASI: Evolutionary Adversarial Simulator Identification for Sim-to-Real Transfer. - Yang Zhou, Tan Li Hui Faith, Yanyu Xu, Sicong Leng, Xinxing Xu, Yong Liu, Rick Siow Mong Goh:
BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays. - Awni Altabaa, Zhuoran Yang:
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games. - Ziqiao Wang, Yongyi Mao:
On $f$-Divergence Principled Domain Adaptation: An Improved Framework. - Woo Kyung Kim, Youngseok Lee, Jooyoung Kim, Honguk Woo:
LLM-based Skill Diffusion for Zero-shot Policy Adaptation. - Zhen Chen, Yi Zhang, Fu Wang, Xingyu Zhao, Xiaowei Huang, Wenjie Ruan:
TARP-VP: Towards Evaluation of Transferred Adversarial Robustness and Privacy on Label Mapping Visual Prompting Models. - Antonio Terpin, Nicolas Lanzetti, Martín Gadea, Florian Dörfler:
Learning diffusion at lightspeed. - Zechen Bai, Tong He, Haiyang Mei, Pichao Wang, Ziteng Gao, Joya Chen, Lei Liu, Zheng Zhang, Mike Zheng Shou:
One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos. - Wei Yu, Bowen Yang, Qinglin Liu, Jianing Li, Shengping Zhang, Xiangyang Ji:
Rethinking Imbalance in Image Super-Resolution for Efficient Inference. - Boqiang Zhang, Zuan Gao, Yadong Qu, Hongtao Xie:
How Control Information Influences Multilingual Text Image Generation and Editing? - Jesus Zarzar, Bernard Ghanem:
SplitNeRF: Split Sum Approximation Neural Field for Joint Geometry, Illumination, and Material Estimation. - Kai Sandbrink, Jan P. Bauer, Alexandra M. Proca, Andrew M. Saxe, Christopher Summerfield, Ali Hummos:
Flexible task abstractions emerge in linear networks with fast and bounded units. - Deepak Sridhar, Abhishek Peri, Rohith Rachala, Nuno Vasconcelos:
Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis. - Weihao Lu, Haobo Zhang, Yicheng Li, Qian Lin:
On the Saturation Effects of Spectral Algorithms in Large Dimensions. - Tianjing Zhang, Yuhui Quan, Hui Ji:
Cross-Scale Self-Supervised Blind Image Deblurring via Implicit Neural Representation. - Yuanning Cui, Zequn Sun, Wei Hu:
A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning. - Ali Younis, Erik B. Sudderth:
Learning to be Smooth: An End-to-End Differentiable Particle Smoother. - Lingxiao Zhao, Xueying Ding, Leman Akoglu:
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation. - Weichao Zhao, Hao Feng, Qi Liu, Jingqun Tang, Binghong Wu, Lei Liao, Shu Wei, Yongjie Ye, Hao Liu, Wengang Zhou, Houqiang Li, Can Huang:
TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy. - Chujie Gao, Siyuan Wu, Yue Huang, Dongping Chen, Qihui Zhang, Zhengyan Fu, Yao Wan, Lichao Sun, Xiangliang Zhang:
HonestLLM: Toward an Honest and Helpful Large Language Model. - Tianle Gu, Zeyang Zhou, Kexin Huang, Dandan Liang, Yixu Wang, Haiquan Zhao, Yuanqi Yao, Xingge Qiao, Keqing Wang, Yujiu Yang, Yan Teng, Yu Qiao, Yingchun Wang:
MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models. - Yiheng Wang, Tianyu Wang, YuYing Zhang, Hongji Zhang, Haoyu Zheng, Guanjie Zheng, Linghe Kong:
UrbanDataLayer: A Unified Data Pipeline for Urban Science. - Thomas W. Mitchel, Michael J. Taylor, Vincent Sitzmann:
Neural Isometries: Taming Transformations for Equivariant ML. - Yutao Sun, Li Dong, Yi Zhu, Shaohan Huang, Wenhui Wang, Shuming Ma, Quanlu Zhang, Jianyong Wang, Furu Wei:
You Only Cache Once: Decoder-Decoder Architectures for Language Models. - Xingyu Zhou, Komo (Wei) Zhang:
Locally Private and Robust Multi-Armed Bandits. - Samyadeep Basu, Martin Grayson, Cecily Morrison, Besmira Nushi, Soheil Feizi, Daniela Massiceti:
Understanding Information Storage and Transfer in Multi-Modal Large Language Models. - Bin Ren, Yawei Li, Jingyun Liang, Rakesh Ranjan, Mengyuan Liu, Rita Cucchiara, Luc Van Gool, Ming-Hsuan Yang, Nicu Sebe:
Sharing Key Semantics in Transformer Makes Efficient Image Restoration. - Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang:
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. - Zhe Zhao, Haibin Wen, Zikang Wang, Pengkun Wang, Fanfu Wang, Song Lai, Qingfu Zhang, Yang Wang:
Breaking Long-Tailed Learning Bottlenecks: A Controllable Paradigm with Hypernetwork-Generated Diverse Experts. - Haipeng Luo, Spandan Senapati, Vatsal Sharan:
Optimal Multiclass U-Calibration Error and Beyond. - Mohammad Sadil Khan, Sankalp Sinha, Talha Uddin Sheikh, Didier Stricker, Sk Aziz Ali, Muhammad Zeshan Afzal:
Text2CAD: Generating Sequential CAD Designs from Beginner-to-Expert Level Text Prompts. - Xuanyu Yi, Zike Wu, Qiuhong Shen, Qingshan Xu, Pan Zhou, Joo-Hwee Lim, Shuicheng Yan, Xinchao Wang, Hanwang Zhang:
MVGamba: Unify 3D Content Generation as State Space Sequence Modeling. - Ang Bian, Wei Li, Hangjie Yuan, Chengrong Yu, Mang Wang, Zixiang Zhao, Aojun Lu, Pengliang Ji, Tao Feng:
Make Continual Learning Stronger via C-Flat. - Jonathan Thomm, Giacomo Camposampiero, Aleksandar Terzic, Michael Hersche, Bernhard Schölkopf, Abbas Rahimi:
Limits of Transformer Language Models on Learning to Compose Algorithms. - Xiaoge Deng, Tao Sun, Shengwei Li, Dongsheng Li, Xicheng Lu:
Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness. - Yubo Ye, Maryam Toloubidokhti, Sumeet Vadhavkar, Xiajun Jiang, Huafeng Liu, Linwei Wang:
On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution. - Gongfan Fang, Hongxu Yin, Saurav Muralidharan, Greg Heinrich, Jeff Pool, Jan Kautz, Pavlo Molchanov, Xinchao Wang:
MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models. - Divyansh Pareek, Simon S. Du, Sewoong Oh:
Understanding the Gains from Repeated Self-Distillation. - Dongfang Li, Zhenyu Liu, Xinshuo Hu, Zetian Sun, Baotian Hu, Min Zhang:
In-Context Learning State Vector with Inner and Momentum Optimization. - Yuxuan Tong, Xiwen Zhang, Rui Wang, Ruidong Wu, Junxian He:
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving. - Ori Press, Andreas Hochlehnert, Ameya Prabhu, Vishaal Udandarao, Ofir Press, Matthias Bethge:
CiteME: Can Language Models Accurately Cite Scientific Claims? - Yue Lu, Shizhou Zhang, De Cheng, Yinghui Xing, Nannan Wang, Peng Wang, Yanning Zhang:
Visual Prompt Tuning in Null Space for Continual Learning. - Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna:
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. - Polina Turishcheva, Max F. Burg, Fabian H. Sinz, Alexander S. Ecker:
Reproducibility of predictive networks for mouse visual cortex. - Rohan Baskar Prabhakar, Hengrui Zhang, David Wentzlaff:
Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference. - Hongyu Shen, Yici Yan, Zhizhen Jane Zhao:
DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection. - Cuong Dao, Phi Le Nguyen, Truong Thao Nguyen, Nghia Hoang:
Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques. - Hui Wei, Zhixiang Wang, Kewei Zhang, Jiaqi Hou, Yuanwei Liu, Hao Tang, Zheng Wang:
Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection. - Gang Liu, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Graph Diffusion Transformers for Multi-Conditional Molecular Generation. - Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin, Nathan Lambert, Yejin Choi, Nouha Dziri:
WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs. - Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg:
Reparameterization invariance in approximate Bayesian inference. - Matteo Zecchin, Osvaldo Simeone:
Localized Adaptive Risk Control. - Arjun Subramonian, Jian Kang, Yizhou Sun:
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks. - Michael Crawshaw, Mingrui Liu:
Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis. - Julius Hense, Mina Jamshidi Idaji, Oliver Eberle, Thomas Schnake, Jonas Dippel, Laure Ciernik, Oliver Buchstab, Andreas Mock, Frederick Klauschen, Klaus-Robert Müller:
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology. - Ayush Sawarni, Nirjhar Das, Siddharth Barman, Gaurav Sinha:
Generalized Linear Bandits with Limited Adaptivity. - Gefen Dawidowicz, Elad Hirsch, Ayellet Tal:
Image-aware Evaluation of Generated Medical Reports. - Jiapu Wang, Kai Sun, Linhao Luo, Wei Wei, Yongli Hu, Alan Wee-Chung Liew, Shirui Pan, Baocai Yin:
Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning. - Joowon Lee, Jared D. Huling, Guanhua Chen:
An effective framework for estimating individualized treatment rules. - Taira Tsuchiya, Shinji Ito:
A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $\Theta(T^{2/3})$ and its Application to Best-of-Both-Worlds. - Runze Yang, Longbing Cao, Jie Yang, Jianxun Li:
Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting. - Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco:
Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints. - Guhao Feng, Han Zhong:
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity. - Hao Shao, Shengju Qian, Han Xiao, Guanglu Song, Zhuofan Zong, Letian Wang, Yu Liu, Hongsheng Li:
Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning. - Xuandong Zhao, Kexun Zhang, Zihao Su, Saastha Vasan, Ilya Grishchenko, Christopher Kruegel, Giovanni Vigna, Yu-Xiang Wang, Lei Li:
Invisible Image Watermarks Are Provably Removable Using Generative AI. - Qiang Li, Hoi-To Wai:
Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss. - Ziyu Liu, Tao Chu, Yuhang Zang, Xilin Wei, Xiaoyi Dong, Pan Zhang, Zijian Liang, Yuanjun Xiong, Yu Qiao, Dahua Lin, Jiaqi Wang:
MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs. - Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng, Chengming Zhang, Baixi Sun, Haibin Lin, Zhi Zhang, Xin Liu, Dingwen Tao:
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training. - Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, Tong Zhao:
How Does Message Passing Improve Collaborative Filtering? - Jung-Hun Kim, Milan Vojnovic, Se-Young Yun:
An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints. - Aniket Das, Dheeraj Nagaraj, Soumyabrata Pal, Arun Sai Suggala, Prateek Varshney:
Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD. - Alexander Nikitin, Jannik Kossen, Yarin Gal, Pekka Marttinen:
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities. - Ruochen Liu, Hao Chen, Yuanchen Bei, Qijie Shen, Fangwei Zhong, Senzhang Wang, Jianxin Wang:
Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination. - Jonathan Hayase, Alisa Liu, Yejin Choi, Sewoong Oh, Noah A. Smith:
Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions. - Jörg K. H. Franke, Michael Hefenbrock, Gregor Köhler, Frank Hutter:
Improving Deep Learning Optimization through Constrained Parameter Regularization. - Luke Eilers, Raoul-Martin Memmesheimer, Sven Goedeke:
A generalized neural tangent kernel for surrogate gradient learning. - Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann:
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. - Haiquan Lu, Yefan Zhou, Shiwei Liu, Zhangyang Wang, Michael W. Mahoney, Yaoqing Yang:
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models. - Heeseong Shin, Chaehyun Kim, Sunghwan Hong, Seokju Cho, Anurag Arnab, Paul Hongsuck Seo, Seungryong Kim:
Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels. - Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu:
Sample Efficient Bayesian Learning of Causal Graphs from Interventions. - Shangkun Sun, Jiaming Liu, Huaxia Li, Guoqing Liu, Thomas H. Li, Wei Gao:
StreamFlow: Streamlined Multi-Frame Optical Flow Estimation for Video Sequences. - Sanae Lotfi, Yilun Kuang, Marc Finzi, Brandon Amos, Micah Goldblum, Andrew Gordon Wilson:
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models. - Han Huang, Haitian Zhong, Tao Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark. - Yue Wang, Zhongchang Sun, Shaofeng Zou:
A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch. - Alex Elenter, Spyros Angelopoulos, Christoph Dürr, Yanni Lefki:
Overcoming Brittleness in Pareto-Optimal Learning Augmented Algorithms. - Shirley Wu, Kaidi Cao, Bruno Ribeiro, James Y. Zou, Jure Leskovec:
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts. - Yuhang Wen, Mengyuan Liu, Songtao Wu, Beichen Ding:
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition. - Joel Daniel Andersson, Monika Henzinger, Rasmus Pagh, Teresa Anna Steiner, Jalaj Upadhyay:
Continual Counting with Gradual Privacy Expiration. - Ke Liang, Yue Liu, Hao Li, Lingyuan Meng, Suyuan Liu, Siwei Wang, Sihang Zhou, Xinwang Liu:
Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding. - Fangcong Yin, Xi Ye, Greg Durrett:
LoFiT: Localized Fine-tuning on LLM Representations. - Jie Ma, Min Hu, Pinghui Wang, Wangchun Sun, Lingyun Song, Hongbin Pei, Jun Liu, Youtian Du:
Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering. - Yawar Siddiqui, Tom Monnier, Filippos Kokkinos, Mahendra Kariya, Yanir Kleiman, Emilien Garreau, Oran Gafni, Natalia Neverova, Andrea Vedaldi, Roman Shapovalov, David Novotný:
Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials. - Chunlin Tian, Zhan Shi, Zhijiang Guo, Li Li, Cheng-Zhong Xu:
HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning. - Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Wei Chen:
Graph Diffusion Policy Optimization. - Biao Gong, Shuai Tan, Yutong Feng, Xiaoying Xie, Yuyuan Li, Chaochao Chen, Kecheng Zheng, Yujun Shen, Deli Zhao:
UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training. - Haixiang Sun, Ye Shi:
Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective. - Derui Zhu, Dingfan Chen, Xiongfei Wu, Jiahui Geng, Zhuo Li, Jens Grossklags, Lei Ma:
PrivAuditor: Benchmarking Data Protection Vulnerabilities in LLM Adaptation Techniques. - Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan R. Peters:
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. - Xiang Fu, Andrew S. Rosen, Kyle Bystrom, Rui Wang, Albert Musaelian, Boris Kozinsky, Tess E. Smidt, Tommi S. Jaakkola:
A Recipe for Charge Density Prediction. - Yongcheng Jing, Seok-Hee Hong, Dacheng Tao:
Deep Graph Mating. - Yingzhe Peng, Chenduo Hao, Xinting Hu, Jiawei Peng, Xin Geng, Xu Yang:
LIVE: Learnable In-Context Vector for Visual Question Answering. - Beomseok Kang, Priyabrata Saha, Sudarshan Sharma, Biswadeep Chakraborty, Saibal Mukhopadhyay:
Online Relational Inference for Evolving Multi-agent Interacting Systems. - Hefei Li, Chao Peng, Chenyang Xu, Zhengfeng Yang:
Open-Book Neural Algorithmic Reasoning. - Shahar Yadin, Noam Elata, Tomer Michaeli:
Classification Diffusion Models: Revitalizing Density Ratio Estimation. - Yearang Lee, Ho-Joong Kim, Seong-Whan Lee:
Text-Infused Attention and Foreground-Aware Modeling for Zero-Shot Temporal Action Detection. - Jianyi Yang, Pengfei Li, Adam Wierman, Shaolei Ren:
Online Budgeted Matching with General Bids. - Daniel de Vassimon Manela, Laura Battaglia, Robin J. Evans:
Marginal Causal Flows for Validation and Inference. - Liqiang Lin, Wenpeng Wu, Chi-Wing Fu, Hao Zhang, Hui Huang:
CRAYM: Neural Field Optimization via Camera RAY Matching. - Aaron Defazio, Xingyu Yang, Ahmed Khaled, Konstantin Mishchenko, Harsh Mehta, Ashok Cutkosky:
The Road Less Scheduled. - Mingyi Li, Xiao Zhang, Qi Wang, Tengfei Liu, Ruofan Wu, Weiqiang Wang, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu:
Resource-Aware Federated Self-Supervised Learning with Global Class Representations. - Zhaokun Zhou, Yijie Lu, Yanhao Jia, Kaiwei Che, Jun Niu, Liwei Huang, Xinyu Shi, Yuesheng Zhu, Guoqi Li, Zhaofei Yu, Li Yuan:
Spiking Transformer with Experts Mixture. - Eric Zhao, Pranjal Awasthi, Zhengdao Chen, Sreenivas Gollapudi, Daniel Delling:
Semantic Routing via Autoregressive Modeling. - Peter A. Jansen, Marc-Alexandre Côté, Tushar Khot, Erin Bransom, Bhavana Dalvi Mishra, Bodhisattwa Prasad Majumder, Oyvind Tafjord, Peter Clark:
DiscoveryWorld: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents. - Zifan Liu, Amin Karbasi, Theodoros Rekatsinas:
TSDS: Data Selection for Task-Specific Model Finetuning. - Ashok Cutkosky, Zakaria Mhammedi:
Fully Unconstrained Online Learning. - Andy Yang, David Chiang, Dana Angluin:
Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages. - Sifei Liu, Shalini De Mello, Jan Kautz:
CosAE: Learnable Fourier Series for Image Restoration. - Hyun-Young Park, Shahab Asoodeh, Si-Hyeon Lee:
Exactly Minimax-Optimal Locally Differentially Private Sampling. - Zican Dong, Junyi Li, Xin Men, Xin Zhao, Bingning Wang, Zhen Tian, Weipeng Chen, Ji-Rong Wen:
Exploring Context Window of Large Language Models via Decomposed Positional Vectors. - Adarsh Jamadandi, Celia Rubio-Madrigal, Rebekka Burkholz:
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing. - Shubham Chowdhary, Giulia De Pasquale, Nicolas Lanzetti, Ana-Andreea Stoica, Florian Dörfler:
Fairness in Social Influence Maximization via Optimal Transport. - Yuezhu Xu, S. Sivaranjani:
ECLipsE: Efficient Compositional Lipschitz Constant Estimation for Deep Neural Networks. - Mariia Vladimirova, Federico Pavone, Eustache Diemert:
FairJob: A Real-World Dataset for Fairness in Online Systems. - Xiao Yang, Kai Sun, Hao Xin, Yushi Sun, Nikita Bhalla, Xiangsen Chen, Sajal Choudhary, Rongze Daniel Gui, Ziran Will Jiang, Ziyu Jiang, Lingkun Kong, Brian Moran, Jiaqi Wang, Yifan Xu, An Yan, Chenyu Yang, Eting Yuan, Hanwen Zha, Nan Tang, Lei Chen, Nicolas Scheffer, Yue Liu, Nirav Shah, Rakesh Wanga, Anuj Kumar, Scott Yih, Xin Dong:
CRAG - Comprehensive RAG Benchmark. - Wenyu Du, Tongxu Luo, Zihan Qiu, Zeyu Huang, Yikang Shen, Reynold Cheng, Yike Guo, Jie Fu:
Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training. - David Perera, Victor Letzelter, Théo Mariotte, Adrien Cortés, Mickaël Chen, Slim Essid, Gaël Richard:
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing. - Jaeseok Jang, Hyuk-Yoon Kwon:
Are Multiple Instance Learning Algorithms Learnable for Instances? - Minseon Gwak, Seongrok Moon, Joohwan Ko, PooGyeon Park:
Layer-Adaptive State Pruning for Deep State Space Models. - Matthieu Kirchmeyer, Pedro O. Pinheiro, Saeed Saremi:
Score-based 3D molecule generation with neural fields. - Jiatong Li, Renjun Hu, Kunzhe Huang, Yan Zhuang, Qi Liu, Mengxiao Zhu, Xing Shi, Wei Lin:
PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations. - Yongchun Li, Santanu Dey, Weijun Xie:
On Sparse Canonical Correlation Analysis. - Jiangyuan Li, Jiayi Wang, Raymond K. W. Wong, Kwun Chuen Gary Chan:
A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness. - Weihang Xu, Maryam Fazel, Simon S. Du:
Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models. - Elizabeth Louise Baker, Gefan Yang, Michael L. Severinsen, Christy Anna Hipsley, Stefan Sommer:
Conditioning non-linear and infinite-dimensional diffusion processes. - Yusu Hong, Junhong Lin:
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions. - Po-Wei Huang, Patrick Rebentrost:
Quantum algorithm for large-scale market equilibrium computation. - David P. Woodruff, Samson Zhou:
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters. - Roi Cohen, Konstantin Dobler, Eden Biran, Gerard de Melo:
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token. - Gennaro Gala, Cassio P. de Campos, Antonio Vergari, Erik Quaeghebeur:
Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits. - Tuan Anh Pham, Vikas Garg:
What do Graph Neural Networks learn? Insights from Tropical Geometry. - Takeshi Koshizuka, Masahiro Fujisawa, Yusuke Tanaka, Issei Sato:
Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective. - Xuechen Zhang, Xiangyu Chang, Mingchen Li, Amit K. Roy-Chowdhury, Jiasi Chen, Samet Oymak:
Selective Attention: Enhancing Transformer through Principled Context Control. - Jeremiah Birrell, Reza Ebrahimi, Rouzbeh Behnia, Jason Pacheco:
Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement. - Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
A Simple and Optimal Approach for Universal Online Learning with Gradient Variations. - Xuexun Liu, Xiaoxu Xu, Jinlong Li, Qiudan Zhang, Xu Wang, Nicu Sebe, Lin Ma:
LESS: Label-Efficient and Single-Stage Referring 3D Segmentation. - Maryam Aliakbarpour, Piotr Indyk, Ronitt Rubinfeld, Sandeep Silwal:
Optimal Algorithms for Augmented Testing of Discrete Distributions. - Luca Barsellotti, Roberto Bigazzi, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara:
Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments. - Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han:
Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. - Ziyi Chen, Yan Wen, Zhengmian Hu, Heng Huang:
Robust Reinforcement Learning with General Utility. - Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet:
Addressing Bias in Online Selection with Limited Budget of Comparisons. - Xueying Jiang, Sheng Jin, Xiaoqin Zhang, Ling Shao, Shijian Lu:
MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders. - Matt MacDermott, James Fox, Francesco Belardinelli, Tom Everitt:
Measuring Goal-Directedness. - Liwei Huang, Zhengyu Ma, Liutao Yu, Huihui Zhou, Yonghong Tian:
Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli. - Yijun Liu, Jiequan Cui, Zhuotao Tian, Senqiao Yang, Qingdong He, Xiaoling Wang, Jingyong Su:
Typicalness-Aware Learning for Failure Detection. - David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo, Santiago Góngora, Aishik Mandal, Sukannya Purkayastha, Jesús-Germán Ortiz-Barajas, Emilio Villa-Cueva, Jinheon Baek, Soyeong Jeong, Injy Hamed, Zheng Xin Yong, Zheng Wei Lim, Paula Mónica Silva, Jocelyn Dunstan, Mélanie Jouitteau, David Le Meur, Joan Nwatu, Ganzorig Batnasan, Munkh-Erdene Otgonbold, Munkhjargal Gochoo, Guido Ivetta, Luciana Benotti, Laura Alonso Alemany, Hernán Maina, Jiahui Geng, Tiago Timponi Torrent, Frederico Belcavello, Marcelo Viridiano, Jan Christian Blaise Cruz, Dan John Velasco, Oana Ignat, Zara Burzo, Chenxi Whitehouse, Artem Abzaliev, Teresa Clifford, Grainne Caulfield, Teresa Lynn, Christian Salamea Palacios, Vladimir Araujo, Yova Kementchedjhieva, Mihail Mihaylov, Israel Abebe Azime, Henok Biadglign Ademtew, Bontu Fufa Balcha, Naome A. Etori, David Ifeoluwa Adelani, Rada Mihalcea, Atnafu Lambebo Tonja, Maria Camila Buitrago Cabrera, Gisela Vallejo, Holy Lovenia, Ruochen Zhang, Marcos Estecha-Garitagoitia, Mario Rodríguez-Cantelar, Toqeer Ehsan, Rendi Chevi, Muhammad Farid Adilazuarda, Ryandito Diandaru, Samuel Cahyawijaya, Fajri Koto, Tatsuki Kuribayashi, Haiyue Song, Aditya Khandavally, Thanmay Jayakumar, Raj Dabre, Mohamed Fazli Mohamed Imam, Kumaranage Ravindu Yasas Nagasinghe, Alina Dragonetti, Luis Fernando D'Haro, Olivier Niyomugisha, Jay Gala, Pranjal A. Chitale, Fauzan Farooqui, Thamar Solorio, Alham Fikri Aji:
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark. - Dong Huang, Yuhao Qing, Weiyi Shang, Heming Cui, Jie Zhang:
EffiBench: Benchmarking the Efficiency of Automatically Generated Code. - George Tsoukalas, Jasper Lee, John Jennings, Jimmy Xin, Michelle Ding, Michael Jennings, Amitayush Thakur, Swarat Chaudhuri:
PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition. - Dongsu Lee, Minhae Kwon:
Episodic Future Thinking Mechanism for Multi-agent Reinforcement Learning. - Jindong Jiang, Fei Deng, Gautam Singh, Minseung Lee, Sungjin Ahn:
Slot State Space Models. - Yongwei Nie, Mingxian Fan, Chengjiang Long, Qing Zhang, Jian Zhu, Xuemiao Xu:
Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recovery. - Yu Xiang, Jie Qiao, Zefeng Liang, Zihuai Zeng, Ruichu Cai, Zhifeng Hao:
On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function. - Chunan Liu, Lilian Denzler, Yihong Chen, Andrew Martin, Brooks Paige:
AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction. - Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent:
Variational Flow Matching for Graph Generation. - Jaehee Kim, Yukyung Lee, Pilsung Kang:
A Gradient Accumulation Method for Dense Retriever under Memory Constraint. - Haicang Zhou, Weiming Huang, Yile Chen, Tiantian He, Gao Cong, Yew Soon Ong:
Road Network Representation Learning with the Third Law of Geography. - Haizhou Du, Yijian Chen, Ryan Yang, Yuchen Li, Linghe Kong:
HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links. - Gwanghyun Kim, Alonso Martinez, Yu-Chuan Su, Brendan Jou, José Lezama, Agrim Gupta, Lijun Yu, Lu Jiang, Aren Jansen, Jacob Walker, Krishna Somandepalli:
A Versatile Diffusion Transformer with Mixture of Noise Levels for Audiovisual Generation. - Haoran Lu, Ruihai Wu, Yitong Li, Sijie Li, Ziyu Zhu, Chuanruo Ning, Yan Zhao, Longzan Luo, Yuanpei Chen, Hao Dong:
GarmentLab: A Unified Simulation and Benchmark for Garment Manipulation. - Hayden McTavish, Jon Donnelly, Margo I. Seltzer, Cynthia Rudin:
Interpretable Generalized Additive Models for Datasets with Missing Values. - Fangcheng Liu, Yehui Tang, Zhenhua Liu, Yunsheng Ni, Duyu Tang, Kai Han, Yunhe Wang:
Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exiting. - Yiwen Qiu, Yujia Zheng, Kun Zhang:
Identifying Selections for Unsupervised Subtask Discovery. - Barna Pásztor, Parnian Kassraie, Andreas Krause:
Bandits with Preference Feedback: A Stackelberg Game Perspective. - Sanghyun Son, Matheus Gadelha, Yang Zhou, Zexiang Xu, Ming C. Lin, Yi Zhou:
DMesh: A Differentiable Mesh Representation. - Jacob Silberg, Kyle Swanson, Elana Simon, Angela Zhang, Zaniar Ghazizadeh, Scott Ogden, Hisham Hamadeh, James Y. Zou:
UniTox: Leveraging LLMs to Curate a Unified Dataset of Drug-Induced Toxicity from FDA Labels. - Xingkui Zhu, Yiran Guan, Dingkang Liang, Yuchao Chen, Yuliang Liu, Xiang Bai:
MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks. - Rongzhe Wei, Eli Chien, Pan Li:
Differentially Private Graph Diffusion with Applications in Personalized PageRanks. - Jialin Luo, Yuanzhi Wang, Ziqi Gu, Yide Qiu, Shuaizhen Yao, Fuyun Wang, Chunyan Xu, Wenhua Zhang, Dan Wang, Zhen Cui:
MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation. - Mingjia Li, Shuang Li, Tongrui Su, Longhui Yuan, Jian Liang, Wei Li:
Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation. - Wang Lin, Jingyuan Chen, Jiaxin Shi, Zirun Guo, Yichen Zhu, Zehan Wang, Tao Jin, Zhou Zhao, Fei Wu, Shuicheng Yan, Hanwang Zhang:
Action Imitation in Common Action Space for Customized Action Image Synthesis. - Xin Cai, Zhiyuan You, Hailong Zhang, Jinwei Gu, Wentao Liu, Tianfan Xue:
PhoCoLens: Photorealistic and Consistent Reconstruction in Lensless Imaging. - Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun:
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage. - Delin Qu, Qizhi Chen, Pingrui Zhang, Xianqiang Gao, Bin Zhao, Zhigang Wang, Dong Wang, Xuelong Li:
LiveScene: Language Embedding Interactive Radiance Fields for Physical Scene Control and Rendering. - Kairan Zhao, Meghdad Kurmanji, George-Octavian Barbulescu, Eleni Triantafillou, Peter Triantafillou:
What makes unlearning hard and what to do about it. - Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin:
The Power of Resets in Online Reinforcement Learning. - Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov:
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning. - Hao Bai, Yifei Zhou, Jiayi Pan, Mert Cemri, Alane Suhr, Sergey Levine, Aviral Kumar:
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning. - Nikita Starodubcev, Mikhail Khoroshikh, Artem Babenko, Dmitry Baranchuk:
Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps. - Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet:
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms. - Jiabao Ji, Yujian Liu, Yang Zhang, Gaowen Liu, Ramana Kompella, Sijia Liu, Shiyu Chang:
Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference. - Lei Zhu, Fangyun Wei, Yanye Lu, Dong Chen:
Scaling the Codebook Size of VQ-GAN to 100, 000 with a Utilization Rate of 99%. - Domenic Rosati, Jan Wehner, Kai Williams, Lukasz Bartoszcze, Robie Gonzales, Carsten Maple, Subhabrata Majumdar, Hassan Sajjad, Frank Rudzicz:
Representation Noising: A Defence Mechanism Against Harmful Finetuning. - Changdae Oh, Hyesu Lim, Mijoo Kim, Dongyoon Han, Sangdoo Yun, Jaegul Choo, Alexander Hauptmann, Zhi-Qi Cheng, Kyungwoo Song:
Towards Calibrated Robust Fine-Tuning of Vision-Language Models. - Peiran Dong, Bingjie Wang, Song Guo, Junxiao Wang, Jie Zhang, Zicong Hong:
Towards Safe Concept Transfer of Multi-Modal Diffusion via Causal Representation Editing. - Hongyi Zhou, Denis Blessing, Ge Li, Onur Celik, Xiaogang Jia, Gerhard Neumann, Rudolf Lioutikov:
Variational Distillation of Diffusion Policies into Mixture of Experts. - Peng Tan, Hai-Tian Liu, Zhi-Hao Tan, Zhi-Hua Zhou:
Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation. - Woosung Kim, Hayeong Lee, Jongmin Lee, Byung-Jun Lee:
ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making. - Shinsaku Sakaue, Taihei Oki:
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming. - Sijie Zhao, Yong Zhang, Xiaodong Cun, Shaoshu Yang, Muyao Niu, Xiaoyu Li, Wenbo Hu, Ying Shan:
CV-VAE: A Compatible Video VAE for Latent Generative Video Models. - Jingyi Zhang, Jiaxing Huang, Xiaoqin Zhang, Ling Shao, Shijian Lu:
Historical Test-time Prompt Tuning for Vision Foundation Models. - Sobihan Surendran, Adeline Fermanian, Antoine Godichon-Baggioni, Sylvain Le Corff:
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation. - Keegan Harris, Zhiwei Steven Wu, Maria-Florina Balcan:
Regret Minimization in Stackelberg Games with Side Information. - Haiyang Huang, Yingfan Wang, Cynthia Rudin:
Navigating the Effect of Parametrization for Dimensionality Reduction. - Yuqi Wang, Ke Cheng, Jiawei He, Qitai Wang, Hengchen Dai, Yuntao Chen, Fei Xia, Zhao-Xiang Zhang:
DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model. - Qiang Wu, Gechang Yao, Zhixi Feng, Shuyuan Yang:
Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis. - Chenlin Zhou, Han Zhang, Zhaokun Zhou, Liutao Yu, Liwei Huang, Xiaopeng Fan, Li Yuan, Zhengyu Ma, Huihui Zhou, Yonghong Tian:
QKFormer: Hierarchical Spiking Transformer using Q-K Attention. - Yongzhe Jia, Xuyun Zhang, Hongsheng Hu, Kim-Kwang Raymond Choo, Lianyong Qi, Xiaolong Xu, Amin Beheshti, Wanchun Dou:
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices. - Miles Hutson, Isaac Kauvar, Nick Haber:
Policy-shaped prediction: avoiding distractions in model-based reinforcement learning. - Pham Duy Khanh, Hoang-Chau Luong, Boris S. Mordukhovich, Dat Ba Tran:
Fundamental Convergence Analysis of Sharpness-Aware Minimization. - Ariel D. Procaccia, Ben Schiffer, Shirley Zhang:
Honor Among Bandits: No-Regret Learning for Online Fair Division. - Boris Repasky, Ehsan Abbasnejad, Anthony R. Dick:
BLURD: Benchmarking and Learning using a Unified Rendering and Diffusion Model. - Tianyu He, Darshil Doshi, Aritra Das, Andrey Gromov:
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks. - Hanyue Lou, Jinxiu (Sherry) Liang, Minggui Teng, Bin Fan, Yong Xu, Boxin Shi:
Zero-Shot Event-Intensity Asymmetric Stereo via Visual Prompting from Image Domain. - Junyu Lu, Bo Xu, Xiaokun Zhang, Hongbo Wang, Haohao Zhu, Dongyu Zhang, Liang Yang, Hongfei Lin:
Towards Comprehensive Detection of Chinese Harmful Memes. - Tariq Berrada Ifriqi, Pietro Astolfi, Melissa Hall, Reyhane Askari Hemmat, Yohann Benchetrit, Marton Havasi, Matthew J. Muckley, Karteek Alahari, Adriana Romero-Soriano, Jakob Verbeek, Michal Drozdzal:
On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. - Xinyu Zhao, Guoheng Sun, Ruisi Cai, Yukun Zhou, Pingzhi Li, Peihao Wang, Bowen Tan, Yexiao He, Li Chen, Yi Liang, Beidi Chen, Binhang Yuan, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen:
Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild. - Peng Wang, Songshuo Lu, Yaohua Tang, Sijie Yan, Wei Xia, Yuanjun Xiong:
A Full-duplex Speech Dialogue Scheme Based On Large Language Model. - Takeshi Noda, Chao Chen, Weiqi Zhang, Xinhai Liu, Yu-Shen Liu, Zhizhong Han:
MultiPull: Detailing Signed Distance Functions by Pulling Multi-Level Queries at Multi-Step. - Hongzhi Ruan, Haibao Yu, Wenxian Yang, Siqi Fan, Zaiqing Nie:
Learning Cooperative Trajectory Representations for Motion Forecasting. - Matthew Dowling, Yuan Zhao, Memming Park:
eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling. - Louis Serrano, Thomas X. Wang, Etienne Le Naour, Jean-Noël Vittaut, Patrick Gallinari:
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields. - Hang Guo, Tao Dai, Yuanchao Bai, Bin Chen, Xudong Ren, Zexuan Zhu, Shu-Tao Xia:
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts. - Paul Couairon, Mustafa Shukor, Jean-Emmanuel Haugeard, Matthieu Cord, Nicolas Thome:
DiffCut: Catalyzing Zero-Shot Semantic Segmentation with Diffusion Features and Recursive Normalized Cut. - James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai:
BitDelta: Your Fine-Tune May Only Be Worth One Bit. - Zhe Liu, Jinghua Hou, Xinyu Wang, Xiaoqing Ye, Jingdong Wang, Hengshuang Zhao, Xiang Bai:
LION: Linear Group RNN for 3D Object Detection in Point Clouds. - Yinshuang Xu, Dian Chen, Katherine Liu, Sergey Zakharov, Rares Ambrus, Kostas Daniilidis, Vitor Guizilini:
$SE(3)$ Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation. - Zheng Zhan, Yushu Wu, Yifan Gong, Zichong Meng, Zhenglun Kong, Changdi Yang, Geng Yuan, Pu Zhao, Wei Niu, Yanzhi Wang:
Fast and Memory-Efficient Video Diffusion Using Streamlined Inference. - Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi, Viswanath Ganapathy, Shreya Kadambi, Rafael Esteves, Shubhankar Borse, Paul N. Whatmough, Risheek Garrepalli, Mart van Baalen, Harris Teague, Markus Nagel:
Sparse High Rank Adapters. - Nithish Kannen, Arif Ahmad, Marco Andreetto, Vinodkumar Prabhakaran, Utsav Prabhu, Adji Bousso Dieng, Pushpak Bhattacharyya, Shachi Dave:
Beyond Aesthetics: Cultural Competence in Text-to-Image Models. - Jeonghwan Cheon, Sang Wan Lee, Se-Bum Paik:
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport. - Quanling Meng, Qinglin Liu, Zonglin Li, Xiangyuan Lan, Shengping Zhang, Liqiang Nie:
High-Resolution Image Harmonization with Adaptive-Interval Color Transformation. - Yuhui Quan, Tianxiang Zheng, Hui Ji:
Pseudo-Siamese Blind-spot Transformers for Self-Supervised Real-World Denoising. - Marcel Kollovieh, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann:
Expected Probabilistic Hierarchies. - Seon-Ho Lee, Jue Wang, Zhikang Zhang, David Fan, Xinyu Li:
Video Token Merging for Long Video Understanding. - Juhao Liang, Zhenyang Cai, Jianqing Zhu, Huang Huang, Kewei Zong, Bang An, Mosen Alharthi, Juncai He, Lian Zhang, Haizhou Li, Benyou Wang, Jinchao Xu:
Alignment at Pre-training! Towards Native Alignment for Arabic LLMs. - Tristan Cinquin, Marvin Pförtner, Vincent Fortuin, Philipp Hennig, Robert Bamler:
FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning. - Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines:
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning. - Ziyi Liu, Idan Attias, Dan Roy:
Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood. - Ieva Petrulionyte, Julien Mairal, Michael Arbel:
Functional Bilevel Optimization for Machine Learning. - Zhezhe Jiao, Martin Keller-Ressel:
Emergence of heavy tails in homogenized stochastic gradient descent. - Zhongwang Zhang, Pengxiao Lin, Zhiwei Wang, Yaoyu Zhang, Zhi-Qin John Xu:
Initialization is Critical to Whether Transformers Fit Composite Functions by Reasoning or Memorizing. - Xuan Huang, Hanhui Li, Wanquan Liu, Xiaodan Liang, Yiqiang Yan, Yuhao Cheng, Chenqiang Gao:
Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars. - Arpit Agarwal, Eric Balkanski:
Learning-Augmented Dynamic Submodular Maximization. - Xinping Chen, Xiao Ke, Wenzhong Guo:
IF-Font: Ideographic Description Sequence-Following Font Generation. - Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. - Xiaobin Li, Kai Wu, Yujian Betterest Li, Xiaoyu Zhang, Handing Wang, Jing Liu:
Pretrained Optimization Model for Zero-Shot Black Box Optimization. - Alex Jinpeng Wang, Linjie Li, Yiqi Lin, Min Li, Lijuan Wang, Mike Zheng Shou:
Leveraging Visual Tokens for Extended Text Contexts in Multi-Modal Learning. - Ruihao Zheng, Zhenkun Wang:
Boundary Decomposition for Nadir Objective Vector Estimation. - Steven D. Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob N. Foerster, Amanda Prorok:
Recurrent Reinforcement Learning with Memoroids. - Wenhao Wang, Yifan Sun, Zhentao Tan, Yi Yang:
Image Copy Detection for Diffusion Models. - Jiamu Bai, Daoyuan Chen, Bingchen Qian, Liuyi Yao, Yaliang Li:
Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources. - Egor Gladin, Pavel E. Dvurechenskii, Alexander Mielke, Jia-Jie Zhu:
Interaction-Force Transport Gradient Flows. - Junxi Xiao, Qinliang Su:
TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing. - Arthur da Cunha, Mikael Møller Høgsgaard, Kasper Green Larsen:
Optimal Parallelization of Boosting. - Tianyi Qiu, Yang Zhang, Xuchuan Huang, Jasmine Xinze Li, Jiaming Ji, Yaodong Yang:
ProgressGym: Alignment with a Millennium of Moral Progress. - Thomas Kwa, Drake Thomas, Adrià Garriga-Alonso:
Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification. - Xingchi Li, Guanxun Li, Xianyang Zhang:
Segmenting Watermarked Texts From Language Models. - Alaia Solko-Breslin, Seewon Choi, Ziyang Li, Neelay Velingker, Rajeev Alur, Mayur Naik, Eric Wong:
Data-Efficient Learning with Neural Programs. - Yuan He, Moy Yuan, Jiaoyan Chen, Ian Horrocks:
Language Models as Hierarchy Encoders. - Shivang Rawat, David J. Heeger, Stefano Martiniani:
Unconditional stability of a recurrent neural circuit implementing divisive normalization. - Che Liu, Cheng Ouyang, Sibo Cheng, Anand Shah, Wenjia Bai, Rossella Arcucci:
G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training. - Xinyi Wu, Amir Ajorlou, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie:
On the Role of Attention Masks and LayerNorm in Transformers. - Aaron Mishkin, Ahmed Khaled, Yuanhao Wang, Aaron Defazio, Robert M. Gower:
Directional Smoothness and Gradient Methods: Convergence and Adaptivity. - Haiji Liang, Ruize Han:
OVT-B: A New Large-Scale Benchmark for Open-Vocabulary Multi-Object Tracking. - Yang Xu, Yihong Gu, Cong Fang:
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing. - Xiaokun Feng, Xuchen Li, Shiyu Hu, Dailing Zhang, Meiqi Wu, Jing Zhang, Xiaotang Chen, Kaiqi Huang:
MemVLT: Vision-Language Tracking with Adaptive Memory-based Prompts. - Mingrui Zhang, Chunyang Wang, Stephan C. Kramer, Joseph G. Wallwork, Siyi Li, Jiancheng Liu, Xiang Chen, Matthew D. Piggott:
Towards Universal Mesh Movement Networks. - Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang:
Natural Counterfactuals With Necessary Backtracking. - Changwoo Lee, Soo Min Kwon, Qing Qu, Hun-Seok Kim:
BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference. - Yiping Wang, Yifang Chen, Wendan Yan, Alex Fang, Wenjing Zhou, Kevin G. Jamieson, Simon S. Du:
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning. - Xiaoxing Wang, Xiaohan Qin, Xiaokang Yang, Junchi Yan:
ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization. - Shengyuan Chen, Qinggang Zhang, Junnan Dong, Wen Hua, Qing Li, Xiao Huang:
Entity Alignment with Noisy Annotations from Large Language Models. - Qiyao Liang, Ziming Liu, Mitchell Ostrow, Ila Fiete:
How Diffusion Models Learn to Factorize and Compose. - Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Durmus:
Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality. - Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Yannick Kirchhoff, Maximilian Rokuss, Ziyan Huang, Jin Ye, Junjun He, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Saikat Roy, Klaus H. Maier-Hein, Paul F. Jaeger, Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, Yong Xia, Zhaohu Xing, Lei Zhu, Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari, Reza Azad, Dorit Merhof, Pengcheng Shi, Ting Ma, Yuxin Du, Fan Bai, Tiejun Huang, Bo Zhao, Haonan Wang, Xiaomeng Li, Hanxue Gu, Haoyu Dong, Jichen Yang, Maciej A. Mazurowski, Saumya Gupta, Linshan Wu, Jia-Xin Zhuang, Hao Chen, Holger Roth, Daguang Xu, Matthew B. Blaschko, Sergio Decherchi, Andrea Cavalli, Alan L. Yuille, Zongwei Zhou:
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation? - Rongzhen Wang, Chenyu Zheng, Guoqiang Wu, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li:
Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization. - Taejong Joo, Diego Klabjan:
Improving self-training under distribution shifts via anchored confidence with theoretical guarantees. - Haiyu Zhang, Xinyuan Chen, Yaohui Wang, Xihui Liu, Yunhong Wang, Yu Qiao:
4Diffusion: Multi-view Video Diffusion Model for 4D Generation. - Yiran Zhao, Wenxuan Zhang, Guizhen Chen, Kenji Kawaguchi, Lidong Bing:
How do Large Language Models Handle Multilingualism? - Hongyao Tang, Glen Berseth:
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn. - Fanghua Ye, Mingming Yang, Jianhui Pang, Longyue Wang, Derek F. Wong, Emine Yilmaz, Shuming Shi, Zhaopeng Tu:
Benchmarking LLMs via Uncertainty Quantification. - Walter Simoncini, Andrei Bursuc, Spyridon Gidaris, Yuki M. Asano:
No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations. - Zihan Liu, Wei Ping, Rajarshi Roy, Peng Xu, Chankyu Lee, Mohammad Shoeybi, Bryan Catanzaro:
ChatQA: Surpassing GPT-4 on Conversational QA and RAG. - Jihao Andreas Lin, Shreyas Padhy, Bruno Mlodozeniec, Javier Antorán, José Miguel Hernández-Lobato:
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes. - Hao Ma, Tianyi Hu, Zhiqiang Pu, Boyin Liu, Xiaolin Ai, Yanyan Liang, Min Chen:
Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement Learning. - Austin Coursey, Junyi Ji, Marcos Quiñones-Grueiro, William Barbour, Yuhang Zhang, Tyler Derr, Gautam Biswas, Daniel B. Work:
FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event Detection. - Diba Hashemi, Lie He, Martin Jaggi:
CoBo: Collaborative Learning via Bilevel Optimization. - Xiao Tan, Yiqin Wang, Yangyang Shen, Dian Shen, Meng Wang, Peibo Duan, Beilun Wang:
FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings. - Shraddha Barke, Emmanuel Anaya Gonzalez, Saketh Ram Kasibatla, Taylor Berg-Kirkpatrick, Nadia Polikarpova:
HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis. - Anshul Gupta, Samy Tafasca, Arya Farkhondeh, Pierre Vuillecard, Jean-Marc Odobez:
MTGS: A Novel Framework for Multi-Person Temporal Gaze Following and Social Gaze Prediction. - Chengxing Xie, Canyu Chen, Feiran Jia, Ziyu Ye, Shiyang Lai, Kai Shu, Jindong Gu, Adel Bibi, Ziniu Hu, David Jurgens, James Evans, Philip Torr, Bernard Ghanem, Guohao Li:
Can Large Language Model Agents Simulate Human Trust Behavior? - Yuxin Xiao, Chaoqun Wan, Yonggang Zhang, Wenxiao Wang, Binbin Lin, Xiaofei He, Xu Shen, Jieping Ye:
Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control. - Pragya Singh, Ritvik Budhiraja, Ankush Gupta, Anshul Goswami, Mohan Kumar, Pushpendra Singh:
EEVR: A Dataset of Paired Physiological Signals and Textual Descriptions for Joint Emotion Representation Learning. - Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Joanna Matthiesen, Kevin A. Smith, Josh Tenenbaum:
Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads. - Xiaoyue Xu, Qinyuan Ye, Xiang Ren:
Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack. - Yangjun Ruan, Chris J. Maddison, Tatsunori B. Hashimoto:
Observational Scaling Laws and the Predictability of Langauge Model Performance. - Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Yi Liang, Craig Boutilier:
Embedding-Aligned Language Models. - Richard Nock, Yishay Mansour:
How to Boost Any Loss Function. - Harit Vishwakarma, Yi Chen, Sui Jiet Tay, Satya Sai Srinath Namburi, Frederic Sala, Ramya Korlakai Vinayak:
Pearls from Pebbles: Improved Confidence Functions for Auto-labeling. - Zhaoyang Sun, Shengwu Xiong, Yaxiong Chen, Fei Du, Weihua Chen, Fan Wang, Yi Rong:
SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models. - Li Ma, Haoyu Han, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang:
Mixture of Link Predictors on Graphs. - Alexander Rutherford, Michael Beukman, Timon Willi, Bruno Lacerda, Nick Hawes, Jakob N. Foerster:
No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery. - Raj Agrawal, Sam Witty, Andy Zane, Elias Bingham:
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions. - Xiayan Ji, Anton Xue, Eric Wong, Oleg Sokolsky, Insup Lee:
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties. - Kaibo Zhang, Yunjuan Wang, Raman Arora:
Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation. - Xiao Yu, Yuang Qi, Kejiang Chen, Guoqiang Chen, Xi Yang, Pengyuan Zhu, Xiuwei Shang, Weiming Zhang, Nenghai Yu:
DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection. - Rakshit Trivedi, Akbir Khan, Jesse Clifton, Lewis Hammond, Edgar A. Duéñez-Guzmán, Dipam Chakraborty, John P. Agapiou, Jayd Matyas, Alexander Sasha Vezhnevets, Barna Pásztor, Yunke Ao, Omar G. Younis, Jiawei Huang, Benjamin Swain, Haoyuan Qin, Mian Deng, Ziwei Deng, Utku Erdoganaras, Yue Zhao, Marko Tesic, Natasha Jaques, Jakob N. Foerster, Vincent Conitzer, José Hernández-Orallo, Dylan Hadfield-Menell, Joel Z. Leibo:
Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. - Zhengfei Kuang, Shengqu Cai, Hao He, Yinghao Xu, Hongsheng Li, Leonidas J. Guibas, Gordon Wetzstein:
Collaborative Video Diffusion: Consistent Multi-video Generation with Camera Control. - Hee Jae Kim, Kathakoli Sengupta, Masaki Kuribayashi, Hernisa Kacorri, Eshed Ohn-Bar:
Text to Blind Motion. - Min Jae Song:
Cryptographic Hardness of Score Estimation. - Alexander Braun, Sherry Sarkar:
The Secretary Problem with Predicted Additive Gap. - Ruslan Svirschevski, Avner May, Zhuoming Chen, Beidi Chen, Zhihao Jia, Max Ryabinin:
SpecExec: Massively Parallel Speculative Decoding For Interactive LLM Inference on Consumer Devices. - Kevin Christian Wibisono, Yixin Wang:
From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When. - Lingao Xiao, Yang He:
Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation? - Chenghua Guo, Han Yu, Jiaxin Liu, Chao Chen, Qi Li, Sihong Xie, Xi Zhang:
Linear Uncertainty Quantification of Graphical Model Inference. - Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington:
4+3 Phases of Compute-Optimal Neural Scaling Laws. - Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler:
Learning Mixtures of Unknown Causal Interventions. - Hongfu Gao, Feipeng Zhang, Wenyu Jiang, Jun Shu, Feng Zheng, Hongxin Wei:
On the Noise Robustness of In-Context Learning for Text Generation. - Mingzhe Du, Anh Tuan Luu, Bin Ji, Qian Liu, See-Kiong Ng:
Mercury: A Code Efficiency Benchmark for Code Large Language Models. - Tianwei Xiong, Yuqing Wang, Daquan Zhou, Zhijie Lin, Jiashi Feng, Xihui Liu:
LVD-2M: A Long-take Video Dataset with Temporally Dense Captions. - Tongle Wu, Ying Sun:
Implicit Regularization of Decentralized Gradient Descent for Sparse Regression. - Prajwal Singhania, Siddharth Singh, Shwai He, Soheil Feizi, Abhinav Bhatele:
Loki: Low-rank Keys for Efficient Sparse Attention. - Yang Li, Shaobo Han, Jonathan Shihao Ji:
VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks. - Hanchen Xia, Weidong Liu, Xiaojun Mao:
ST$_k$: A Scalable Module for Solving Top-k Problems. - Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams, Petrus Mikkola, Marcelo Hartmann, Kai Puolamäki, Arto Klami:
Non-geodesically-convex optimization in the Wasserstein space. - Qiujiang Jin, Ruichen Jiang, Aryan Mokhtari:
Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search. - Shen Li, Yuyang Zhang, Zhaolin Ren, Claire Liang, Na Li, Julie A. Shah:
Enhancing Preference-based Linear Bandits via Human Response Time. - Scott R. Jeen, Tom Bewley, Jonathan M. Cullen:
Zero-Shot Reinforcement Learning from Low Quality Data. - Chang-Wei Shi, Yi-Rui Yang, Wu-Jun Li:
Ordered Momentum for Asynchronous SGD. - Amir Hossein Kargaran, François Yvon, Hinrich Schütze:
GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages. - Esraa Elelimy, Adam White, Michael Bowling, Martha White:
Real-Time Recurrent Learning using Trace Units in Reinforcement Learning. - Baiqi Li, Zhiqiu Lin, Wenxuan Peng, Jean de Dieu Nyandwi, Daniel Jiang, Zixian Ma, Simran Khanuja, Ranjay Krishna, Graham Neubig, Deva Ramanan:
NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples. - Shreyas Chaudhari, Ameet Deshpande, Bruno C. da Silva, Philip S. Thomas:
Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation. - Jiahao Ying, Yixin Cao, Yushi Bai, Qianru Sun, Bo Wang, Wei Tang, Zhaojun Ding, Yizhe Yang, Xuanjing Huang, Shuicheng Yan:
Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models. - Yizun Lin, Zhao-Rong Lai, Cheng Li:
A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization. - Juntao Dai, Tianle Chen, Xuyao Wang, Ziran Yang, Taiye Chen, Jiaming Ji, Yaodong Yang:
SafeSora: Towards Safety Alignment of Text2Video Generation via a Human Preference Dataset. - Yannis Karmim, Marc Lafon, Raphaël Fournier-S'niehotta, Nicolas Thome:
Supra-Laplacian Encoding for Transformer on Dynamic Graphs. - Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas J. Spanos, Adam Wierman, Ming Jin:
Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. - Daehee Lee, Minjong Yoo, Woo Kyung Kim, Wonje Choi, Honguk Woo:
Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation. - Apurv Shukla, Debabrota Basu:
Preference-based Pure Exploration. - Zhongchang Sun, Sihong He, Fei Miao, Shaofeng Zou:
Policy Optimization for Robust Average Reward MDPs. - Jiaxu Leng, Zhanjie Wu, Mingpi Tan, Yiran Liu, Ji Gan, Haosheng Chen, Xinbo Gao:
Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection. - Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang:
Learning Discrete Latent Variable Structures with Tensor Rank Conditions. - Christopher Blöcker, Chester Tan, Ingo Scholtes:
The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks. - Jianan Yang, Chenchao Gao, Zhiqing Xiao, Junbo Zhao, Sai Wu, Gang Chen, Haobo Wang:
Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild. - Charbel Sakr, Brucek Khailany:
ESPACE: Dimensionality Reduction of Activations for Model Compression. - Zhanhao Hu, Julien Piet, Geng Zhao, Jiantao Jiao, David A. Wagner:
Toxicity Detection for Free. - Fei Ni, Jianye Hao, Shiguang Wu, Longxin Kou, Yifu Yuan, Zibin Dong, Jinyi Liu, MingZhi Li, Yuzheng Zhuang, Yan Zheng:
PERIA: Perceive, Reason, Imagine, Act via Holistic Language and Vision Planning for Manipulation. - Yigit Ekin, Ahmet Burak Yildirim, Erdem Eren Caglar, Aykut Erdem, Erkut Erdem, Aysegul Dundar:
CLIPAway: Harmonizing focused embeddings for removing objects via diffusion models. - Nikita P. Kalinin, Christoph H. Lampert:
Banded Square Root Matrix Factorization for Differentially Private Model Training. - Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Bayesian-guided Label Mapping for Visual Reprogramming. - Haogeng Liu, Quanzeng You, Xiaotian Han, Yongfei Liu, Huaibo Huang, Ran He, Hongxia Yang:
Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model. - Max Hamilton, Christian Lange, Elijah Cole, Alexander Shepard, Samuel Heinrich, Oisin Mac Aodha, Grant Van Horn, Subhransu Maji:
Combining Observational Data and Language for Species Range Estimation. - Matthew Wallingford, Anand Bhattad, Aditya Kusupati, Vivek Ramanujan, Matt Deitke, Aniruddha Kembhavi, Roozbeh Mottaghi, Wei-Chiu Ma, Ali Farhadi:
From an Image to a Scene: Learning to Imagine the World from a Million 360° Videos. - Juexiao Zhang, Gao Zhu, Sihang Li, Xinhao Liu, Haorui Song, Xinran Tang, Chen Feng:
Multiview Scene Graph. - Kyoungseok Jang, Junpei Komiyama, Kazutoshi Yamazaki:
Fixed Confidence Best Arm Identification in the Bayesian Setting. - Xiaojuan Tang, Jiaqi Li, Yitao Liang, Song-Chun Zhu, Muhan Zhang, Zilong Zheng:
Mars: Situated Inductive Reasoning in an Open-World Environment. - Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Qi Long, Li Shen:
Fairness-Aware Estimation of Graphical Models. - Jiawei Chen, Chunhui Zhao:
Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment. - Yi-Shan Wu, Yijie Zhang, Badr-Eddine Chérief-Abdellatif, Yevgeny Seldin:
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss. - Sri Harsha Dumpala, Aman Jaiswal, Chandramouli Shama Sastry, Evangelos E. Milios, Sageev Oore, Hassan Sajjad:
SUGARCREPE++ Dataset: Vision-Language Model Sensitivity to Semantic and Lexical Alterations. - Sangyun Shin, Yuhang He, Madhu Vankadari, Ta Ying Cheng, Qian Xie, Andrew Markham, Niki Trigoni:
Towards Learning Group-Equivariant Features for Domain Adaptive 3D Detection. - Dingshuo Chen, Zhixun Li, Yuyan Ni, Guibin Zhang, Ding Wang, Qiang Liu, Shu Wu, Jeffrey Xu Yu, Liang Wang:
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization. - Yilun Jin, Zheng Li, Chenwei Zhang, Tianyu Cao, Yifan Gao, Pratik Jayarao, Mao Li, Xin Liu, Ritesh Sarkhel, Xianfeng Tang, Haodong Wang, Zhengyang Wang, Wenju Xu, Jingfeng Yang, Qingyu Yin, Xian Li, Priyanka Nigam, Yi Xu, Kai Chen, Qiang Yang, Meng Jiang, Bing Yin:
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models. - Minui Hong, Junhyeog Yun, Insu Jeon, Gunhee Kim:
FedAvP: Augment Local Data via Shared Policy in Federated Learning. - Diego Doimo, Alessandro Serra, Alessio Ansuini, Alberto Cazzaniga:
The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models. - Zhaorui Tan, Xi Yang, Qiufeng Wang, Anh Nguyen, Kaizhu Huang:
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual Classification. - Yeonguk Yu, Minhwan Ko, Sungho Shin, Kangmin Kim, Kyoobin Lee:
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise. - Matthijs Pals, A Erdem Sagtekin, Felix Pei, Manuel Glöckler, Jakob H. Macke:
Inferring stochastic low-rank recurrent neural networks from neural data. - Corinna Cortes, Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong:
Cardinality-Aware Set Prediction and Top-$k$ Classification. - Ruiqi Zhang, Jingfeng Wu, Peter L. Bartlett:
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization. - Xin Hu, Xiaole Tang, Ruixuan Yu, Jian Sun:
Learning 3D Equivariant Implicit Function with Patch-Level Pose-Invariant Representation. - Bo Liu, Lemeng Wu, Lizhang Chen, Kaizhao Liang, Jiaxu Zhu, Chen Liang, Raghuraman Krishnamoorthi, Qiang Liu:
Communication Efficient Distributed Training with Distributed Lion. - MohammadTaghi Hajiaghayi, Shayan Chashm Jahan, Mohammad Sharifi, Suho Shin, Max Springer:
Fairness and Efficiency in Online Class Matching. - MohammadTaghi Hajiaghayi, Sébastien Lahaie, Keivan Rezaei, Suho Shin:
Ad Auctions for LLMs via Retrieval Augmented Generation. - Chong Mou, Mingdeng Cao, Xintao Wang, Zhaoyang Zhang, Ying Shan, Jian Zhang:
ReVideo: Remake a Video with Motion and Content Control. - Adithya Bhaskar, Alexander Wettig, Dan Friedman, Danqi Chen:
Finding Transformer Circuits With Edge Pruning. - Xiaotong Li, Fan Zhang, Haiwen Diao, Yueze Wang, Xinlong Wang, Lingyu Duan:
DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception. - Declan McNamara, Jackson Loper, Jeffrey Regier:
Globally Convergent Variational Inference. - Robi Bhattacharjee, Ulrike von Luxburg:
Auditing Local Explanations is Hard. - Xinyu Xu, Yizheng Zhang, Yonglu Li, Lei Han, Cewu Lu:
HumanVLA: Towards Vision-Language Directed Object Rearrangement by Physical Humanoid. - Samin Yeasar Arnob, Riyasat Ohib, Sergey M. Plis, Amy Zhang, Alessandro Sordoni, Doina Precup:
Efficient Reinforcement Learning by Discovering Neural Pathways. - Jonathan Roberts, Kai Han, Neil Houlsby, Samuel Albanie:
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation. - Megan Tjandrasuwita, Jie Xu, Armando Solar-Lezama, Wojciech Matusik:
MeMo: Meaningful, Modular Controllers via Noise Injection. - Lisha Chen, A. F. M. Saif, Yanning Shen, Tianyi Chen:
FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning. - Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Carlee Joe-Wong, Gina C. Adam, Nathaniel D. Bastian, Tian Lan:
RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space. - Eva Giboulot, Teddy Furon:
WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off. - Daeho Um, Ji Won Yoon, Seong-Jin Ahn, Yunha Yeo:
Gene-Gene Relationship Modeling Based on Genetic Evidence for Single-Cell RNA-Seq Data Imputation. - Benyuan Meng, Qianqian Xu, Zitai Wang, Zhiyong Yang, Xiaochun Cao, Qingming Huang:
Suppress Content Shift: Better Diffusion Features via Off-the-Shelf Generation Techniques. - Xiong-Hui Chen, Ziyan Wang, Yali Du, Shengyi Jiang, Meng Fang, Yang Yu, Jun Wang:
Policy Learning from Tutorial Books via Understanding, Rehearsing and Introspecting. - Ismail Alkhouri, Shijun Liang, Evan Bell, Qing Qu, Rongrong Wang, Saiprasad Ravishankar:
Image Reconstruction Via Autoencoding Sequential Deep Image Prior. - Aleksandros Sobczyk, Marko Mladenovic, Mathieu Luisier:
Invariant subspaces and PCA in nearly matrix multiplication time. - Chaolong Ying, Xinjian Zhao, Tianshu Yu:
Boosting Graph Pooling with Persistent Homology. - Yanmin Wu, Jiarui Meng, Haijie Li, Chenming Wu, Yahao Shi, Xinhua Cheng, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang, Jian Zhang:
OpenGaussian: Towards Point-Level 3D Gaussian-based Open Vocabulary Understanding. - Ioannis Caragiannis, Evi Micha, Nisarg Shah:
Proportional Fairness in Non-Centroid Clustering. - Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon:
PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher. - Zhen Huang, Zengzhi Wang, Shijie Xia, Xuefeng Li, Haoyang Zou, Ruijie Xu, Run-Ze Fan, Lyumanshan Ye, Ethan Chern, Yixin Ye, Yikai Zhang, Yuqing Yang, Ting Wu, Binjie Wang, Shichao Sun, Yang Xiao, Yiyuan Li, Fan Zhou, Steffi Chern, Yiwei Qin, Yan Ma, Jiadi Su, Yixiu Liu, Yuxiang Zheng, Shaoting Zhang, Dahua Lin, Yu Qiao, Pengfei Liu:
OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI. - David Debot, Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra:
Interpretable Concept-Based Memory Reasoning. - Yongyuan Liang, Tingqiang Xu, Kaizhe Hu, Guangqi Jiang, Furong Huang, Huazhe Xu:
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion. - Yuqing Wang, Ye He, Molei Tao:
Evaluating the design space of diffusion-based generative models. - Grzegorz Stefanski, Pawel Daniluk, Artur Szumaczuk, Jakub Tkaczuk:
SOI: Scaling Down Computational Complexity by Estimating Partial States of the Model. - Yunzhe Qi, Yikun Ban, Arindam Banerjee, Jingrui He:
Robust Neural Contextual Bandit against Adversarial Corruptions. - Weimin Bai, Yifei Wang, Wenzheng Chen, He Sun:
An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations. - Lin Chen, Xilin Wei, Jinsong Li, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Zehui Chen, Haodong Duan, Lin Bin, Zhenyu Tang, Li Yuan, Yu Qiao, Dahua Lin, Feng Zhao, Jiaqi Wang:
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions. - Hanna Foerster, Robert D. Mullins, Ilia Shumailov, Jamie Hayes:
Beyond Slow Signs in High-fidelity Model Extraction. - Aditya Bommakanti, Harshith Reddy Vonteri, Konstantinos Skitsas, Sayan Ranu, Davide Mottin, Panagiotis Karras:
FUGAL: Feature-fortified Unrestricted Graph Alignment. - Anish Madan, Neehar Peri, Shu Kong, Deva Ramanan:
Revisiting Few-Shot Object Detection with Vision-Language Models. - Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi:
Progressive Entropic Optimal Transport Solvers. - Dorian Baudry, Hugo Richard, Maria Cherifa, Vianney Perchet, Clément Calauzènes:
Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits. - Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon V. Mathis, Riccardo Barbano, Vincent Dutordoir, Emile Mathieu, Urszula Julia Komorowska, Pietro Lió:
DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform. - Anthony Fuller, Daniel G. Kyrollos, Yousef Yassin, James R. Green:
LookHere: Vision Transformers with Directed Attention Generalize and Extrapolate. - Yan Huang, Xiang Li, Yipeng Shen, Niao He, Jinming Xu:
Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes. - Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael C. Mozer, Sanjeev Arora:
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. - Yonghan Jung, Min Woo Park, Sanghack Lee:
Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference. - Ryoma Yataka, Adriano Cardace, Perry Wang, Petros Boufounos, Ryuhei Takahashi:
RETR: Multi-View Radar Detection Transformer for Indoor Perception. - Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini:
On the Scalability of GNNs for Molecular Graphs. - Yinxuan Huang, Chengmin Gao, Bin Li, Xiangyang Xue:
Improving Viewpoint-Independent Object-Centric Representations through Active Viewpoint Selection. - Yixuan Xu, Hanrui Zhang, Yu Cheng, Vincent Conitzer:
Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction. - Jieyu Zhang, Weikai Huang, Zixian Ma, Oscar Michel, Dong He, Tanmay Gupta, Wei-Chiu Ma, Ali Farhadi, Aniruddha Kembhavi, Ranjay Krishna:
Task Me Anything. - Kai Chen, Yiyao Ma, Xingyu Lin, Stephen James, Jianshu Zhou, Yun-Hui Liu, Pieter Abbeel, Qi Dou:
Vision Foundation Model Enables Generalizable Object Pose Estimation. - Deepak Ravikumar, Efstathia Soufleri, Kaushik Roy:
Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature. - Chen Hang, Zhe Ma, Haoming Chen, Xuwei Fang, Vincent Xie, Faming Fang, Guixu Zhang, Hongbin Wang:
Exploring Fixed Point in Image Editing: Theoretical Support and Convergence Optimization. - Zunnan Xu, Yukang Lin, Haonan Han, Sicheng Yang, Ronghui Li, Yachao Zhang, Xiu Li:
MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models. - Yann Bourreau, Marco Bressan, T.-H. Hubert Chan, Qipeng Kuang, Mauro Sozio:
Efficient Streaming Algorithms for Graphlet Sampling. - Zhenzhi Wang, Yixuan Li, Yanhong Zeng, Youqing Fang, Yuwei Guo, Wenran Liu, Jing Tan, Kai Chen, Tianfan Xue, Bo Dai, Dahua Lin:
HumanVid: Demystifying Training Data for Camera-controllable Human Image Animation. - Eyar Azar, Boaz Nadler:
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data. - Sunghyeon Woo, Baeseong Park, Byeongwook Kim, Minjung Jo, Se Jung Kwon, Dongsuk Jeon, Dongsoo Lee:
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation. - Andrew Szot, Bogdan Mazoure, Harsh Agrawal, R. Devon Hjelm, Zsolt Kira, Alexander Toshev:
Grounding Multimodal Large Language Models in Actions. - Adela Frances DePavia, Olga Medrano Martín del Campo, Erasmo Tani:
Optimal Algorithms for Learning Partitions with Faulty Oracles. - Ning Ding, Yehui Tang, Haochen Qin, Zhenli Zhou, Chao Xu, Lin Li, Kai Han, Heng Liao, Yunhe Wang:
MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers. - Zeng Tao, Tong Yang, Junxiong Lin, Xinji Mai, Haoran Wang, Beining Wang, Enyu Zhou, Yan Wang, Wenqiang Zhang:
LCGen: Mining in Low-Certainty Generation for View-consistent Text-to-3D. - Yunwei Ren, Zixuan Wang, Jason D. Lee:
Learning and Transferring Sparse Contextual Bigrams with Linear Transformers. - Bei Li, Tong Zheng, Rui Wang, Jiahao Liu, Qingyan Guo, Junliang Guo, Xu Tan, Tong Xiao, Jingbo Zhu, Jingang Wang, Xunliang Cai:
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning. - Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora:
Public-data Assisted Private Stochastic Optimization: Power and Limitations. - Xixi Jia, Fangchen Feng, Deyu Meng, Defeng Sun:
Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing. - Zhenxiong Tan, Kaixin Wang, Xinchao Wang:
Implicit Curriculum in Procgen Made Explicit. - Daiqing Qi, Handong Zhao, Sheng Li:
Easy Regional Contrastive Learning of Expressive Fashion Representations. - Guanyu Nie, Vaneet Aggarwal, Christopher J. Quinn:
Gradient Methods for Online DR-Submodular Maximization with Stochastic Long-Term Constraints. - Weiyun Wang, Shuibo Zhang, Yiming Ren, Yuchen Duan, Tiantong Li, Shuo Liu, Mengkang Hu, Zhe Chen, Kaipeng Zhang, Lewei Lu, Xizhou Zhu, Ping Luo, Yu Qiao, Jifeng Dai, Wenqi Shao, Wenhai Wang:
Needle In A Multimodal Haystack. - Artur Szalata, Andrew Benz, Robrecht Cannoodt, Mauricio Cortes, Jason Fong, Sunil Kuppasani, Richard Lieberman, Tianyu Liu, Javier Mas-Rosario, Rico Meinl, Jalil Nourisa, Jared Tumiel, Tin M. Tunjic, Mengbo Wang, Noah Weber, Hongyu Zhao, Benedict Anchang, Fabian J. Theis, Malte Luecken, Daniel Burkhardt:
A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types. - Zhou Fang, Yong-Lu Li, Lixin Yang, Cewu Lu:
General Articulated Objects Manipulation in Real Images via Part-Aware Diffusion Process. - Noah Golowich, Ankur Moitra:
Edit Distance Robust Watermarks via Indexing Pseudorandom Codes. - Kanan Gupta, Jonathan W. Siegel, Stephan Wojtowytsch:
Nesterov acceleration despite very noisy gradients. - Chandramouli Shama Sastry, Sri Harsha Dumpala, Sageev Oore:
DiffAug: A Diffuse-and-Denoise Augmentation for Training Robust Classifiers. - Jiaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang:
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective. - Nicolás Astorga, Tennison Liu, Nabeel Seedat, Mihaela van der Schaar:
Active Learning with LLMs for Partially Observed and Cost-Aware Scenarios. - Minghui Chen, Meirui Jiang, Xin Zhang, Qi Dou, Zehua Wang, Xiaoxiao Li:
Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning. - Di Ming, Peng Ren, Yunlong Wang, Xin Feng:
Boosting the Transferability of Adversarial Attack on Vision Transformer with Adaptive Token Tuning. - Zhenwei Tang, Difan Jiao, Reid McIlroy-Young, Jon M. Kleinberg, Siddhartha Sen, Ashton Anderson:
Maia-2: A Unified Model for Human-AI Alignment in Chess. - Yuan Qiu, Nolan Bridges, Peng Chen:
Derivative-enhanced Deep Operator Network. - Shogo Iwazaki, Shinya Suzumura:
No-Regret Bandit Exploration based on Soft Tree Ensemble Model. - Hoin Jung, Taeuk Jang, Xiaoqian Wang:
A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks. - Eleonora Gualdoni, Mycal Tucker, Roger Levy, Noga Zaslavsky:
Bridging semantics and pragmatics in information-theoretic emergent communication. - Tom Sander, Pierre Fernandez, Alain Durmus, Matthijs Douze, Teddy Furon:
Watermarking Makes Language Models Radioactive. - Natalie Maus, Kyurae Kim, David Eriksson, Geoff Pleiss, John P. Cunningham, Jacob R. Gardner:
Approximation-Aware Bayesian Optimization. - Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park:
Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features. - Siwei Tu, Weidong Yang, Ben Fei:
Taming Generative Diffusion Prior for Universal Blind Image Restoration. - Taewon Park, Hyun-Chul Kim, Minho Lee:
Discrete Dictionary-based Decomposition Layer for Structured Representation Learning. - Shenghai Yuan, Jinfa Huang, Yongqi Xu, Yaoyang Liu, Shaofeng Zhang, Yujun Shi, Ruijie Zhu, Xinhua Cheng, Jiebo Luo, Li Yuan:
ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation. - Jonas Kulhanek, Songyou Peng, Zuzana Kukelova, Marc Pollefeys, Torsten Sattler:
WildGaussians: 3D Gaussian Splatting In the Wild. - Boxuan Zhang, Jianing Zhu, Zengmao Wang, Tongliang Liu, Bo Du, Bo Han:
What If the Input is Expanded in OOD Detection? - Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec:
RelBench: A Benchmark for Deep Learning on Relational Databases. - Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He:
PageRank Bandits for Link Prediction. - Zhiqi Li, Yiming Chen, Peidong Liu:
DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation. - Bin Fan, Jiaoyang Yin, Yuchao Dai, Chao Xu, Tiejun Huang, Boxin Shi:
Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras. - Aleksandr V. Lobanov, Alexander V. Gasnikov, Andrey Krasnov:
Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values. - Andreas Schlaginhaufen, Maryam Kamgarpour:
Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning. - Jiahao Wang, Caixia Yan, Haonan Lin, Weizhan Zhang, Mengmeng Wang, Tieliang Gong, Guang Dai, Hao Sun:
OneActor: Consistent Subject Generation via Cluster-Conditioned Guidance. - Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis:
Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models. - Zhengyi Li, Kang Yang, Jin Tan, Wen-jie Lu, Haoqi Wu, Xiao Wang, Yu Yu, Derun Zhao, Yancheng Zheng, Minyi Guo, Jingwen Leng:
Nimbus: Secure and Efficient Two-Party Inference for Transformers. - Misha Khodak, Lester Mackey, Alexandra Chouldechova, Miro Dudík:
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation. - Rebecca Saul, Chang Liu, Noah Fleischmann, Richard Zak, Kristopher K. Micinski, Edward Raff, James Holt:
Is Function Similarity Over-Engineered? Building a Benchmark. - Levi E. Lingsch, Dana Grund, Siddhartha Mishra, Georgios Kissas:
FUSE: Fast Unified Simulation and Estimation for PDEs. - Dongyan Lucy Huo, Yixuan Zhang, Yudong Chen, Qiaomin Xie:
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize. - Anka Reuel-Lamparth, Amelia F. Hardy, Chandler Smith, Max Lamparth, Malcolm Hardy, Mykel J. Kochenderfer:
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices. - Joel Dyer, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Anisoara Calinescu, Theodoros Damoulas, Michael J. Wooldridge:
Interventionally Consistent Surrogates for Complex Simulation Models. - Yutao Dou, Huimin Yu, Wei Li, Jingyang Li, Fei Xia, Jian Xiao:
PEACE: A Dataset of Pharmaceutical Care for Cancer Pain Analgesia Evaluation and Medication Decision. - Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao:
Depth Anything V2. - Jacopo Dapueto, Nicoletta Noceti, Francesca Odone:
Transferring disentangled representations: bridging the gap between synthetic and real images. - Zehui Li, Yuhao Ni, Guoxuan Xia, William A. V. Beardall, Akashaditya Das, Guy-Bart Stan, Yiren Zhao:
Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences. - Jikang Cheng, Zhiyuan Yan, Ying Zhang, Yuhao Luo, Zhongyuan Wang, Chen Li:
Can We Leave Deepfake Data Behind in Training Deepfake Detector? - Dongyu Ru, Lin Qiu, Xiangkun Hu, Tianhang Zhang, Peng Shi, Shuaichen Chang, Cheng Jiayang, Cunxiang Wang, Shichao Sun, Huanyu Li, Zizhao Zhang, Binjie Wang, Jiarong Jiang, Tong He, Zhiguo Wang, Pengfei Liu, Yue Zhang, Zheng Zhang:
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation. - Ted de Vries Lentsch, Holger Caesar, Dariu Gavrila:
UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-Classes. - Wei Jiang, Sifan Yang, Yibo Wang, Lijun Zhang:
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions. - Xinran Li, Ling Pan, Jun Zhang:
Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning. - Kien X. Nguyen, Fengchun Qiao, Arthur Trembanis, Xi Peng:
SeafloorAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey. - Brandon Huang, Chancharik Mitra, Leonid Karlinsky, Assaf Arbelle, Trevor Darrell, Roei Herzig:
Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning. - Baiyu Su, Qiang Liu:
Quadratic Quantum Variational Monte Carlo. - Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer:
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. - Chengsen Wang, Qi Qi, Jingyu Wang, Haifeng Sun, Zirui Zhuang, Jinming Wu, Jianxin Liao:
Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective. - Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun:
Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure. - Eyal Michaeli, Ohad Fried:
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation. - Tianhang Wang, Fan Lu, Zehan Zheng, Zhijun Li, Guang Chen, Changjun Jiang:
RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modeling. - Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Y. Zou, Stefano Ermon:
TFG: Unified Training-Free Guidance for Diffusion Models. - Junjiao Tian, Chengyue Huang, Zsolt Kira:
Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models. - Xiaoshuai Hao, Mengchuan Wei, Yifan Yang, Haimei Zhao, Hui Zhang, Yi Zhou, Qiang Wang, Weiming Li, Lingdong Kong, Jing Zhang:
Is Your HD Map Constructor Reliable under Sensor Corruptions? - Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, Mikhail Yurochkin:
Efficient multi-prompt evaluation of LLMs. - Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang, Lingjuan Lyu, Ang Li:
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations. - Nam Phuong Tran, The-Anh Ta, Shuqing Shi, Debmalya Mandal, Yali Du, Long Tran-Thanh:
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games. - Mingzhen Huang, Jialing Cai, Shan Jia, Vishnu Suresh Lokhande, Siwei Lyu:
ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping. - Regev Cohen, Idan Kligvasser, Ehud Rivlin, Daniel Freedman:
Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models. - Christos Thrampoulidis:
Implicit Optimization Bias of Next-token Prediction in Linear Models. - William Redman, Francisco Acosta, Santiago Acosta-Mendoza, Nina Miolane:
Not so griddy: Internal representations of RNNs path integrating more than one agent. - Haiyun Yao, Zongbo Han, Huazhu Fu, Xi Peng, Qinghua Hu, Changqing Zhang:
Out-Of-Distribution Detection with Diversification (Provably). - Wenjia Xie, Hao Wang, Luankang Zhang, Rui Zhou, Defu Lian, Enhong Chen:
Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model. - Huaijin Wu, Xinyu Ye, Junchi Yan:
QVAE-Mole: The Quantum VAE with Spherical Latent Variable Learning for 3-D Molecule Generation. - Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin G. Jamieson:
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning. - Qi Lv, Xiang Deng, Gongwei Chen, Michael Yu Wang, Liqiang Nie:
Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL. - Nicholas Rittler, Kamalika Chaudhuri:
Distribution Learning with Valid Outputs Beyond the Worst-Case. - Christopher T. H. Teo, Milad Abdollahzadeh, Xinda Ma, Ngai-Man Cheung:
FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation. - Irene Huang, Wei Lin, Muhammad Jehanzeb Mirza, Jacob A. Hansen, Sivan Doveh, Victor Butoi, Roei Herzig, Assaf Arbelle, Hilde Kuehne, Trevor Darrell, Chuang Gan, Aude Oliva, Rogério Feris, Leonid Karlinsky:
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs. - Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, Deming Chen:
SnapKV: LLM Knows What You are Looking for Before Generation. - Yujia Zhou, Zheng Liu, Zhicheng Dou:
Boosting the Potential of Large Language Models with an Intelligent Information Assistant. - Alexander Lappe, Anna Bognár, Ghazaleh Ghamkhari Nejad, Albert Mukovskiy, Lucas Martini, Martin A. Giese, Rufin Vogels:
Parallel Backpropagation for Shared-Feature Visualization. - Massimiliano Datres, Gian Paolo Leonardi, Alessio Figalli, David Sutter:
A two-scale Complexity Measure for Deep Learning Models. - Zhishuai Guo, Tianbao Yang:
Communication-Efficient Federated Group Distributionally Robust Optimization. - Kamalika Chaudhuri, Po-Ling Loh, Shourya Pandey, Purnamrita Sarkar:
On Differentially Private U Statistics. - Marco Miani, Lorenzo Beretta, Søren Hauberg:
Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information. - Wei Chow, Juncheng Li, Qifan Yu, Kaihang Pan, Hao Fei, Zhiqi Ge, Shuai Yang, Siliang Tang, Hanwang Zhang, Qianru Sun:
Unified Generative and Discriminative Training for Multi-modal Large Language Models. - Francesco D'Angelo, Maksym Andriushchenko, Aditya Vardhan Varre, Nicolas Flammarion:
Why Do We Need Weight Decay in Modern Deep Learning? - Kai Hu, Weichen Yu, Yining Li, Tianjun Yao, Xiang Li, Wenhe Liu, Lijun Yu, Zhiqiang Shen, Kai Chen, Matt Fredrikson:
Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization. - Aliaksandra Shysheya, Cristiana Diaconu, Federico Bergamin, Paris Perdikaris, José Miguel Hernández-Lobato, Richard E. Turner, Emile Mathieu:
On conditional diffusion models for PDE simulations. - Jonas Ngnawé, Sabyasachi Sahoo, Yann Pequignot, Frédéric Precioso, Christian Gagné:
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers. - Wanghan Xu, Fenghua Ling, Wenlong Zhang, Tao Han, Hao Chen, Wanli Ouyang, Lei Bai:
Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling. - Yunpeng Gong, Zhun Zhong, Yansong Qu, Zhiming Luo, Rongrong Ji, Min Jiang:
Cross-Modality Perturbation Synergy Attack for Person Re-identification. - Yamin Li, Ange Lou, Ziyuan Xu, Shengchao Zhang, Shiyu Wang, Dario J. Englot, Soheil Kolouri, Daniel Moyer, Roza G. Bayrak, Catie Chang:
NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mapping. - Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng:
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms. - Manuel Dahnert, Angela Dai, Norman Müller, Matthias Nießner:
Coherent 3D Scene Diffusion From a Single RGB Image. - Lingchen Meng, Jianwei Yang, Rui Tian, Xiyang Dai, Zuxuan Wu, Jianfeng Gao, Yu-Gang Jiang:
DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs. - Zenan Li, Zhi Zhou, Yuan Yao, Xian Zhang, Yu-Feng Li, Chun Cao, Fan Yang, Xiaoxing Ma:
Neuro-Symbolic Data Generation for Math Reasoning. - Guande He, Kaiwen Zheng, Jianfei Chen, Fan Bao, Jun Zhu:
Consistency Diffusion Bridge Models. - Benjamin Hoover, Duen Horng Chau, Hendrik Strobelt, Parikshit Ram, Dmitry Krotov:
Dense Associative Memory Through the Lens of Random Features. - Jin-Hwi Park, Hae-Gon Jeon:
A Simple yet Universal Framework for Depth Completion. - William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic:
Identifying Equivalent Training Dynamics. - Yingjun Shen, Haizhao Dai, Qihe Chen, Yan Zeng, Jiakai Zhang, Yuan Pei, Jingyi Yu:
DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM. - Liulei Li, Wenguan Wang, Yi Yang:
Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models. - David Janz, Alexander E. Litvak, Csaba Szepesvári:
Ensemble sampling for linear bandits: small ensembles suffice. - Mohammad-Amin Charusaie, Samira Samadi:
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems. - Shan Chen, Jack Gallifant, Mingye Gao, Pedro Moreira, Nikolaj Munch, Ajay Muthukkumar, Arvind Rajan, Jaya Kolluri, Amelia Fiske, Janna Hastings, Hugo J. W. L. Aerts, Brian Anthony, Leo Anthony Celi, William G. La Cava, Danielle S. Bitterman:
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias. - Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, El Houcine Bergou:
If You Want to Be Robust, Be Wary of Initialization. - Haoqun Cao, Zizhuo Meng, Tianjun Ke, Feng Zhou:
Is Score Matching Suitable for Estimating Point Processes? - Nivasini Ananthakrishnan, Nika Haghtalab, Chara Podimata, Kunhe Yang:
Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions. - Bochuan Cao, Jinyuan Jia, Chuxuan Hu, Wenbo Guo, Zhen Xiang, Jinghui Chen, Bo Li, Dawn Song:
Data Free Backdoor Attacks. - Chenyu Yang, Xizhou Zhu, Jinguo Zhu, Weijie Su, Junjie Wang, Xuan Dong, Wenhai Wang, Bin Li, Jie Zhou, Yu Qiao, Jifeng Dai:
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning. - Zirui Yan, Ali Tajer:
Linear Causal Bandits: Unknown Graph and Soft Interventions. - Chenyang Zhang, Difan Zou, Yuan Cao:
The Implicit Bias of Adam on Separable Data. - Abhimanyu Hans, John Kirchenbauer, Yuxin Wen, Neel Jain, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein:
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. - Yang Zhou, Zhuoming Chen, Zhaozhuo Xu, Victoria Lin, Beidi Chen:
SIRIUS : Contexual Sparisty with Correction for Efficient LLMs. - Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann:
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion. - Yuki Minai, Joana Soldado-Magraner, Matthew A. Smith, Byron M. Yu:
MiSO: Optimizing brain stimulation to create neural activity states. - Hanlin Gu, WinKent Ong, Chee Seng Chan, Lixin Fan:
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity. - Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei W. Koh, Bryan Hooi:
Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs. - Joscha Cüppers, Sascha Xu, Ahmed Musa, Jilles Vreeken:
Causal Discovery from Event Sequences by Local Cause-Effect Attribution. - João Monteiro, Pierre-André Noël, Étienne Marcotte, Sai Rajeswar Mudumba, Valentina Zantedeschi, David Vázquez, Nicolas Chapados, Chris Pal, Perouz Taslakian:
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content. - Haolin Liu, Artin Tajdini, Andrew Wagenmaker, Chen-Yu Wei:
Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification. - Xiaodan Chen, Xiucheng Li, Xinyang Chen, Zhijun Li:
Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics. - Ioar Casado, Luis A. Ortega Andrés, Aritz Pérez, Andrés R. Masegosa:
PAC-Bayes-Chernoff bounds for unbounded losses. - Jacob Dunefsky, Philippe Chlenski, Neel Nanda:
Transcoders find interpretable LLM feature circuits. - Qian Chen, Tianjian Zhang, Linxin Yang, Qingyu Han, Akang Wang, Ruoyu Sun, Xiaodong Luo, Tsung-Hui Chang:
SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization. - Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli:
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. - Shuo Yu, Shan Jin, Ming Li, Tabinda Sarwar, Feng Xia:
Long-range Brain Graph Transformer. - Kai Hu, Jinhao Li, Yuan Zhang, Xiongjun Ye, Xieping Gao:
One-to-Multiple: A Progressive Style Transfer Unsupervised Domain-Adaptive Framework for Kidney Tumor Segmentation. - Tiancheng Wang, Yuguang Yang, Linlin Yang, Shaohui Lin, Juan Zhang, Guodong Guo, Baochang Zhang:
CLIP in Mirror: Disentangling text from visual images through reflection. - Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, Loris D'Antoni:
Grammar-Aligned Decoding. - Chiara Mastrogiuseppe, Rubén Moreno-Bote:
Controlled maximal variability along with reliable performance in recurrent neural networks. - Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-Kyun Noh, Frank C. Park:
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models. - Naveen Raman, Zheyuan Shi, Fei Fang:
Global Rewards in Restless Multi-Armed Bandits. - Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius:
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression. - Yang Peng, Liangyu Zhang, Zhihua Zhang:
Statistical Efficiency of Distributional Temporal Difference Learning. - Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis:
Faster Repeated Evasion Attacks in Tree Ensembles. - Jia Syuen Lim, Zhuoxiao Chen, Zhi Chen, Mahsa Baktashmotlagh, Xin Yu, Zi Huang, Yadan Luo:
DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection. - Haoran You, Yipin Guo, Yichao Fu, Wei Zhou, Huihong Shi, Xiaofan Zhang, Souvik Kundu, Amir Yazdanbakhsh, Yingyan (Celine) Lin:
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization. - Yufei Guo, Yuanpei Chen, Zecheng Hao, Weihang Peng, Zhou Jie, Yuhan Zhang, Xiaode Liu, Zhe Ma:
Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks. - Meijun Wang, Yu Meng, Zhongwei Qiu, Chao Zheng, Yan Xu, Pengxiaorui, Jian Gao:
Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective. - Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Yusuke Kato, Kazuki Kozuka:
Aligning Diffusion Models by Optimizing Human Utility. - Qijun Luo, Hengxu Yu, Xiao Li:
BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models. - Rayen Dhahri, Alexander Immer, Bertrand Charpentier, Stephan Günnemann, Vincent Fortuin:
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood. - Yifan Yang, Zhaofeng Si, Siwei Lyu, Kaiyi Ji:
First-Order Minimax Bilevel Optimization. - Hongyu Cheng, Sammy Khalife, Barbara Fiedorowicz, Amitabh Basu:
Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut. - Haitao Li, You Chen, Qingyao Ai, Yueyue Wu, Ruizhe Zhang, Yiqun Liu:
LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models. - Yang Liu, Chenchen Jing, Hengtao Li, Muzhi Zhu, Hao Chen, Xinlong Wang, Chunhua Shen:
A Simple Image Segmentation Framework via In-Context Examples. - Tianyi Zhou, Deqing Fu, Vatsal Sharan, Robin Jia:
Pre-trained Large Language Models Use Fourier Features to Compute Addition. - Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter:
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators. - Sharmita Dey, Sarath Ravindran Nair:
ReMAP: Neural Model Reprogramming with Network Inversion and Retrieval-Augmented Mapping for Adaptive Motion Forecasting. - Jialong Zuo, Ying Nie, Hanyu Zhou, Huaxin Zhang, Haoyu Wang, Tianyu Guo, Nong Sang, Changxin Gao:
Cross-video Identity Correlating for Person Re-identification Pre-training. - Shuaifeng Li, Mao Ye, Lihua Zhou, Nianxin Li, Siying Xiao, Song Tang, Xiatian Zhu:
Cloud Object Detector Adaptation by Integrating Different Source Knowledge. - Zijian Zhou, Xiaoqiang Lin, Xinyi Xu, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low:
DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning. - Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba:
Mirror and Preconditioned Gradient Descent in Wasserstein Space. - Heewoong Noh, Namkyeong Lee, Gyoung S. Na, Chanyoung Park:
Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge. - Sattar Vakili, Julia Olkhovskaya:
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm. - Zengzhi Wang, Xuefeng Li, Rui Xia, Pengfei Liu:
MathPile: A Billion-Token-Scale Pretraining Corpus for Math. - Gabriel Nobis, Maximilian Springenberg, Marco Aversa, Michael Detzel, Rembert Daems, Roderick Murray-Smith, Shinichi Nakajima, Sebastian Lapuschkin, Stefano Ermon, Tolga Birdal, Manfred Opper, Christoph Knochenhauer, Luis Oala, Wojciech Samek:
Generative Fractional Diffusion Models. - Xinyue Li, Rishi Sonthalia:
Least Squares Regression Can Exhibit Under-Parameterized Double Descent. - Yuhan Zhu, Yuyang Ji, Zhiyu Zhao, Gangshan Wu, Limin Wang:
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation. - Wenjing Yan, Xuanyu Cao:
Decentralized Noncooperative Games with Coupled Decision-Dependent Distributions. - Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon:
Geometric Trajectory Diffusion Models. - Haibin He, Maoyuan Ye, Jing Zhang, Juhua Liu, Bo Du, Dacheng Tao:
GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching. - Yuheng Shi, Minjing Dong, Chang Xu:
Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model. - Yitao Xu, Tong Zhang, Sabine Süsstrunk:
AdanCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer. - Junfeng Ni, Yixin Chen, Bohan Jing, Nan Jiang, Bin Wang, Bo Dai, Puhao Li, Yixin Zhu, Song-Chun Zhu, Siyuan Huang:
PhyRecon: Physically Plausible Neural Scene Reconstruction. - Mingze Wang, Weinan E:
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling. - Pankaj K. Agarwal, Sharath Raghvendra, Pouyan Shirzadian, Keegan Yao:
A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem. - Yohann Perron, Vladyslav Sydorov, Adam P. Wijker, Damian Evans, Christophe Pottier, Loïc Landrieu:
Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era. - Chenxin Tao, Xizhou Zhu, Shiqian Su, Lewei Lu, Changyao Tian, Xuan Luo, Gao Huang, Hongsheng Li, Yu Qiao, Jie Zhou, Jifeng Dai:
Learning 1D Causal Visual Representation with De-focus Attention Networks. - Leon Lufkin, Andrew M. Saxe, Erin Grant:
Nonlinear dynamics of localization in neural receptive fields. - Vincent Cohen-Addad, Tommaso d'Orsi, Anupam Gupta, Euiwoong Lee, Debmalya Panigrahi:
Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems. - Shirley Wu, Shiyu Zhao, Qian Huang, Kexin Huang, Michihiro Yasunaga, Kaidi Cao, Vassilis N. Ioannidis, Karthik Subbian, Jure Leskovec, James Y. Zou:
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning. - Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin M. Solomon:
Score Distillation via Reparametrized DDIM. - Kaiyan Zhang, Sihang Zeng, Ermo Hua, Ning Ding, Zhang-Ren Chen, Zhiyuan Ma, Haoxin Li, Ganqu Cui, Biqing Qi, Xuekai Zhu, Xingtai Lv, Jinfang Hu, Zhiyuan Liu, Bowen Zhou:
UltraMedical: Building Specialized Generalists in Biomedicine. - Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello:
Smoke and Mirrors in Causal Downstream Tasks. - Felix Petersen, Christian Borgelt, Tobias Sutter, Hilde Kuehne, Oliver Deussen, Stefano Ermon:
Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms. - Chandra Sekhar Mukherjee, Nikhil Deorkar, Jiapeng Zhang:
Capturing the denoising effect of PCA via compression ratio. - Mengxi Zhang, Wenhao Wu, Yu Lu, Yuxin Song, Kang Rong, Huanjin Yao, Jianbo Zhao, Fanglong Liu, Haocheng Feng, Jingdong Wang, Yifan Sun:
Automated Multi-level Preference for MLLMs. - Jialu Li, Yu Wang, Pengfei Zhu, Wanyu Lin, Qinghua Hu:
What Matters in Graph Class Incremental Learning? An Information Preservation Perspective. - Andrew M. Bean, Simi Hellsten, Harry Mayne, Jabez Magomere, Ethan Chi, Ryan Chi, Scott Hale, Hannah Rose Kirk:
LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages. - Jiacheng Cen, Anyi Li, Ning Lin, Yuxiang Ren, Zihe Wang, Wenbing Huang:
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks? - Yiyang Sun, Tong Wang, Cynthia Rudin:
Improving Decision Sparsity. - Qiufeng Wang, Xu Yang, Fu Feng, Jing Wang, Xin Geng:
Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers. - Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang:
Multi-Instance Partial-Label Learning with Margin Adjustment. - Dinh Duc Cao, Seok Joon Kim, Kyusung Cho:
Geometric Exploitation for Indoor Panoramic Semantic Segmentation. - Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He, Tao Li, Xiaolin Huang:
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement. - Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf, Doina Precup, Shuangjia Zheng:
ReactZyme: A Benchmark for Enzyme-Reaction Prediction. - Kimon Protopapas, Anas Barakat:
Policy Mirror Descent with Lookahead. - Andreas Maurer:
Generalization of Hamiltonian algorithms. - Xuxing Chen, Abhishek Roy, Yifan Hu, Krishnakumar Balasubramanian:
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data. - Shervin Khalafi, Dongsheng Ding, Alejandro Ribeiro:
Constrained Diffusion Models via Dual Training. - David Holzmüller, Léo Grinsztajn, Ingo Steinwart:
Better by default: Strong pre-tuned MLPs and boosted trees on tabular data. - Chuanyang Zheng, Yihang Gao, Han Shi, Minbin Huang, Jingyao Li, Jing Xiong, Xiaozhe Ren, Michael K. Ng, Xin Jiang, Zhenguo Li, Yu Li:
DAPE: Data-Adaptive Positional Encoding for Length Extrapolation. - Qidong Liu, Xian Wu, Yejing Wang, Zijian Zhang, Feng Tian, Yefeng Zheng, Xiangyu Zhao:
LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation. - Victor Boone, Zihan Zhang:
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs. - Anton Rodomanov, Xiaowen Jiang, Sebastian U. Stich:
Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction. - Xuan Chen, Yuzhou Nie, Wenbo Guo, Xiangyu Zhang:
When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search. - Ying Yang, De Cheng, Chaowei Fang, Yubiao Wang, Changzhe Jiao, Lechao Cheng, Nannan Wang, Xinbo Gao:
Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection. - Kushagra Pandey, Ruihan Yang, Stephan Mandt:
Fast samplers for Inverse Problems in Iterative Refinement models. - Changze Lv, Dongqi Han, Yansen Wang, Xiaoqing Zheng, Xuanjing Huang, Dongsheng Li:
Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators. - Keyon Vafa, Justin Y. Chen, Ashesh Rambachan, Jon M. Kleinberg, Sendhil Mullainathan:
Evaluating the World Model Implicit in a Generative Model. - Yichun Hu, Nathan Kallus, Xiaojie Mao, Yanchen Wu:
Contextual Linear Optimization with Bandit Feedback. - Tomoya Sakai, Haoxiang Qiu, Takayuki Katsuki, Daiki Kimura, Takayuki Osogami, Tadanobu Inoue:
A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation. - Yuwei Zhang, Tong Xia, Jing Han, Yu Wu, Georgios Rizos, Yang Liu, Mohammed Mosuily, Jagmohan Chauhan, Cecilia Mascolo:
Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking. - Lin Chen, Jinsong Li, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Zehui Chen, Haodong Duan, Jiaqi Wang, Yu Qiao, Dahua Lin, Feng Zhao:
Are We on the Right Way for Evaluating Large Vision-Language Models? - Pratiksha Thaker, Amrith Setlur, Steven Z. Wu, Virginia Smith:
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift. - Jake Cunningham, Giorgio Giannone, Mingtian Zhang, Marc Peter Deisenroth:
Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling. - Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita:
Streaming Bayes GFlowNets. - The Viet Bui, Tien Mai, Thanh Hong Nguyen:
Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning. - Zhiqiang Chen, Guofan Fan, Jinying Gao, Lei Ma, Bo Lei, Tiejun Huang, Shan Yu:
Learning from Pattern Completion: Self-supervised Controllable Generation. - Minjie Wang, Quan Gan, David Wipf, Zheng Zhang, Christos Faloutsos, Weinan Zhang, Muhan Zhang, Zhenkun Cai, Jiahang Li, Zunyao Mao, Yakun Song, Jianheng Tang, Yanlin Zhang, Guang Yang, Chuan Lei, Xiao Qin, Ning Li, Han Zhang, Yanbo Wang, Zizhao Zhang:
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. - Mathieu Carrière, Marc Theveneau, Théo Lacombe:
Diffeomorphic interpolation for efficient persistence-based topological optimization. - Tom Yan, Zachary C. Lipton:
A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning. - Siyi Chen, Huijie Zhang, Minzhe Guo, Yifu Lu, Peng Wang, Qing Qu:
Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing. - Peng Sun, Yi Jiang, Tao Lin:
Efficiency for Free: Ideal Data Are Transportable Representations. - Haoran Luo, Haihong E, Yuhao Yang, Tianyu Yao, Yikai Guo, Zichen Tang, Wentai Zhang, Shiyao Peng, Kaiyang Wan, Meina Song, Wei Lin, Yifan Zhu, Anh Tuan Luu:
Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction. - Jiangwei Weng, Zhiqiang Yan, Ying Tai, Jianjun Qian, Jian Yang, Jun Li:
MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space. - Yuxin Chen, Junfei Tan, An Zhang, Zhengyi Yang, Leheng Sheng, Enzhi Zhang, Xiang Wang, Tat-Seng Chua:
On Softmax Direct Preference Optimization for Recommendation. - Ben Norman, Jeff Clune:
First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs. - Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron C. Courville, Sai Rajeswar Mudumba:
GenRL: Multimodal-foundation world models for generalization in embodied agents. - Letian Peng, Jingbo Shang:
Quantifying and Optimizing Global Faithfulness in Persona-driven Role-playing. - Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh, Di Niu:
Learning Truncated Causal History Model for Video Restoration. - Shady Abu-Hussein, Raja Giryes:
UDPM: Upsampling Diffusion Probabilistic Models. - Weichao Zhou, Wenchao Li:
Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment. - Guoxin Chen, Minpeng Liao, Chengxi Li, Kai Fan:
AlphaMath Almost Zero: Process Supervision without Process. - Ben Adcock, Nick C. Dexter, Sebastian Moraga Scheuermann:
Optimal deep learning of holomorphic operators between Banach spaces. - Jingwu Tang, Gokul Swamy, Fei Fang, Zhiwei Steven Wu:
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard. - Thibault Simonetto, Salah Ghamizi, Maxime Cordy:
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data. - Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Colin Sandon, Omid Saremi:
How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad. - Dong Jing, Xiaolong He, Yutian Luo, Nanyi Fei, Guoxing Yang, Wei Wei, Huiwen Zhao, Zhiwu Lu:
FineCLIP: Self-distilled Region-based CLIP for Better Fine-grained Understanding. - Richard Nock, Mathieu Guillame-Bert:
Generative Forests. - Haochuan Xu, Ninh Pham:
Scalable DBSCAN with Random Projections. - Qihao Zhou, Haishan Ye, Luo Luo:
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity. - Mingshuang Luo, Ruibing Hou, Zhuo Li, Hong Chang, Zimo Liu, Yaowei Wang, Shiguang Shan:
M$^3$GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and Generation. - Haoran Zhang, Junkai Deng, Xuhui Chen, Fei Hou, Wencheng Wang, Hong Qin, Chen Qian, Ying He:
From Transparent to Opaque: Rethinking Neural Implicit Surfaces with $\alpha$-NeuS. - Stefan Pranger, Hana Chockler, Martin Tappler, Bettina Könighofer:
Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning. - Rohan Choudhury, Guanglei Zhu, Sihan Liu, Koichiro Niinuma, Kris Kitani, László A. Jeni:
Don't Look Twice: Faster Video Transformers with Run-Length Tokenization. - Pihe Hu, Shaolong Li, Zhuoran Li, Ling Pan, Longbo Huang:
Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training. - Hanxiao Zhang, Lin Ju, Chan Wu, Jinjing Huang, Youshao Xiao, Zhenglei Zhou, Zhiming Fan, Zhaoxin Huan, Siyuan Li, Fanzhuang Meng, Lei Liang, Xiaolu Zhang, Jun Zhou:
Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models. - Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu:
GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations. - Shihao Tu, Linfeng Cao, Daoze Zhang, Junru Chen, Lvbin Ma, Yin Zhang, Yang Yang:
DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection. - Junke Wang, Yi Jiang, Zehuan Yuan, Bingyue Peng, Zuxuan Wu, Yu-Gang Jiang:
OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation. - Keyi Kong, Xilie Xu, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli:
Perplexity-aware Correction for Robust Alignment with Noisy Preferences. - Derek Lim, Theo Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka:
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof. - Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert:
Probabilistic Graph Rewiring via Virtual Nodes. - Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou, Bo Han, Xiaowen Chu:
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. - Shaoteng Liu, Haoqi Yuan, Minda Hu, Yanwei Li, Yukang Chen, Shu Liu, Zongqing Lu, Jiaya Jia:
RL-GPT: Integrating Reinforcement Learning and Code-as-policy. - Xiaolei Liu, Shaoshuai Li, Kaixin Gao, Binfeng Wang:
A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks. - Bingqiao Luo, Zhen Zhang, Qian Wang, Bingsheng He:
Multi-Chain Graphs of Graphs: A New Approach to Analyzing Blockchain Datasets. - Mingcheng Li, Dingkang Yang, Yang Liu, Shunli Wang, Jiawei Chen, Shuaibing Wang, Jinjie Wei, Yue Jiang, Qingyao Xu, Xiaolu Hou, Mingyang Sun, Ziyun Qian, Dongliang Kou, Lihua Zhang:
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning. - Leo Zhou, Joao Basso, Song Mei:
Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm. - Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber, Christopher Potts, Christopher D. Manning:
MoEUT: Mixture-of-Experts Universal Transformers. - Feipeng Ma, Hongwei Xue, Yizhou Zhou, Guangting Wang, Fengyun Rao, Shilin Yan, Yueyi Zhang, Siying Wu, Mike Zheng Shou, Xiaoyan Sun:
Visual Perception by Large Language Model's Weights. - Yongxin Zhu, Bocheng Li, Hang Zhang, Xin Li, Linli Xu, Lidong Bing:
Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective. - Jr-Jen Chen, Yu-Chien Liao, Hsi-Che Lin, Yu-Chu Yu, Yen-Chun Chen, Yu-Chiang Frank Wang:
ReXTime: A Benchmark Suite for Reasoning-Across-Time in Videos. - Donato Crisostomi, Marco Fumero, Daniele Baieri, Florian Bernard, Emanuele Rodolà:
$C^2M^3$: Cycle-Consistent Multi-Model Merging. - Daniel Dauner, Marcel Hallgarten, Tianyu Li, Xinshuo Weng, Zhiyu Huang, Zetong Yang, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta:
NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking. - Yuhang Li, Changsheng Li, Ruilin Lv, Rongqing Li, Ye Yuan, Guoren Wang:
LaKD: Length-agnostic Knowledge Distillation for Trajectory Prediction with Any Length Observations. - Byoungwoo Park, Jungwon Choi, Sungbin Lim, Juho Lee:
Stochastic Optimal Control for Diffusion Bridges in Function Spaces. - Ziyang Xiao, Dongxiang Zhang, Xiongwei Han, Xiaojin Fu, Wing Yin Yu, Tao Zhong, Sai Wu, Yuan Wang, Jianwei Yin, Gang Chen:
Enhancing LLM Reasoning via Vision-Augmented Prompting. - Jihyung Kil, Zheda Mai, Justin Lee, Arpita Chowdhury, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, Wei-Lun Chao:
MLLM-CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs. - Haoning Wu, Dongxu Li, Bei Chen, Junnan Li:
LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding. - Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, Jonathan Ilgen, Emma Pierson, Pang Wei W. Koh, Yulia Tsvetkov:
MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning. - Qi Song, Tianxiang Gong, Shiqi Gao, Haoyi Zhou, Jianxin Li:
QUEST: Quadruple Multimodal Contrastive Learning with Constraints and Self-Penalization. - Swapnil Bhosale, Haosen Yang, Diptesh Kanojia, Jiankang Deng, Xiatian Zhu:
AV-GS: Learning Material and Geometry Aware Priors for Novel View Acoustic Synthesis. - Andrew Estornell, Yang Liu:
Multi-LLM Debate: Framework, Principals, and Interventions. - Rachel S. Y. Teo, Tan Nguyen:
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts. - Wenfang Yao, Chen Liu, Kejing Yin, William Kwok-Wai Cheung, Jing Qin:
Addressing Asynchronicity in Clinical Multimodal Fusion via Individualized Chest X-ray Generation. - Zhenghao Lin, Zhibin Gou, Yeyun Gong, Xiao Liu, Yelong Shen, Ruochen Xu, Chen Lin, Yujiu Yang, Jian Jiao, Nan Duan, Weizhu Chen:
Not All Tokens Are What You Need for Pretraining. - Yunpeng Qing, Shunyu Liu, Jingyuan Cong, Kaixuan Chen, Yihe Zhou, Mingli Song:
A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective. - Alex Stergiou:
LAVIB: A Large-scale Video Interpolation Benchmark. - Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati:
Chain of Thoughtlessness? An Analysis of CoT in Planning. - Xuehao Cui, Guangyang Wu, Zhenghao Gan, Guangtao Zhai, Xiaohong Liu:
Face2QR: A Unified Framework for Aesthetic, Face-Preserving, and Scannable QR Code Generation. - Archit Sharma, Sedrick Scott Keh, Eric Mitchell, Chelsea Finn, Kushal Arora, Thomas Kollar:
A Critical Evaluation of AI Feedback for Aligning Large Language Models. - Wenzhuo Liu, Fei Zhu, Shijie Ma, Cheng-Lin Liu:
MSPE: Multi-Scale Patch Embedding Prompts Vision Transformers to Any Resolution. - Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan:
Global Convergence in Training Large-Scale Transformers. - Luiz F. O. Chamon, Mohammad Reza Karimi Jaghargh, Anna Korba:
Constrained Sampling with Primal-Dual Langevin Monte Carlo. - Duo Zhou, Christopher Brix, Grani A. Hanasusanto, Huan Zhang:
Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes. - Jie Zhu, Yixiong Chen, Mingyu Ding, Ping Luo, Leye Wang, Jingdong Wang:
MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts. - Zhiyuan Yan, Taiping Yao, Shen Chen, Yandan Zhao, Xinghe Fu, Junwei Zhu, Donghao Luo, Chengjie Wang, Shouhong Ding, Yunsheng Wu, Li Yuan:
DF40: Toward Next-Generation Deepfake Detection. - Jinlin Lai, Justin Domke, Daniel R. Sheldon:
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models. - Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu:
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory. - Ye Tian, Ling Yang, Haotian Yang, Yuan Gao, Yufan Deng, Xintao Wang, Zhaochen Yu, Xin Tao, Pengfei Wan, Di Zhang, Bin Cui:
VideoTetris: Towards Compositional Text-to-Video Generation. - Peter Mørch Groth, Mads Herbert Kerrn, Lars Olsen, Jesper Salomon, Wouter Boomsma:
Kermut: Composite kernel regression for protein variant effects. - Yuchen Hu, Chen Chen, Chao-Han Yang, Chengwei Qin, Pin-Yu Chen, Engsiong Chng, Chao Zhang:
Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models. - Barakeel Fanseu Kamhoua, Huamin Qu:
HOPE: Shape Matching Via Aligning Different K-hop Neighbourhoods. - Jiying Zhang, Zijing Liu, Yu Wang, Bin Feng, Yu Li:
SubgDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning. - Kaushik Sinha:
Non-parametric classification via expand-and-sparsify representation. - Xiaohang Tang, Afonso Marques, Parameswaran Kamalaruban, Ilija Bogunovic:
Adversarially Robust Decision Transformer. - Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian:
Protecting Your LLMs with Information Bottleneck. - Boxiao Pan, Zhan Xu, Chun-Hao Paul Huang, Krishna Kumar Singh, Yang Zhou, Leonidas J. Guibas, Jimei Yang:
ActAnywhere: Subject-Aware Video Background Generation. - Yerram Varun, Rahul Madhavan, Sravanti Addepalli, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain:
Time-Reversal Provides Unsupervised Feedback to LLMs. - Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans:
UQE: A Query Engine for Unstructured Databases. - Ruihan Gao, Kangle Deng, Gengshan Yang, Wenzhen Yuan, Jun-Yan Zhu:
Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation. - Nachiket Kotalwar, Alkis Gotovos, Adish Singla:
Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation. - Chaeyun Jang, Hyungi Lee, Jungtaek Kim, Juho Lee:
Model Fusion through Bayesian Optimization in Language Model Fine-Tuning. - Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa:
Mind the Graph When Balancing Data for Fairness or Robustness. - Xinke Jiang, Rihong Qiu, Yongxin Xu, Wentao Zhang, Yichen Zhu, Ruizhe Zhang, Yuchen Fang, Chu Xu, Junfeng Zhao, Yasha Wang:
RAGraph: A General Retrieval-Augmented Graph Learning Framework. - Chenghao Fan, Zhenyi Lu, Wei Wei, Jie Tian, Xiaoye Qu, Dangyang Chen, Yu Cheng:
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion. - Narine Kokhlikyan, Bargav Jayaraman, Florian Bordes, Chuan Guo, Kamalika Chaudhuri:
Measuring Dejavu Memorization Efficiently. - Tehila Dahan, Kfir Y. Levy:
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML. - Theodore Tsesmelis, Luca Palmieri, Marina Khoroshiltseva, Adeela Islam, Gur Elkin, Ofir Itzhak Shahar, Gianluca Scarpellini, Stefano Fiorini, Yaniv Ohayon, Nadav Alali, Sinem Aslan, Pietro Morerio, Sebastiano Vascon, Elena Gravina, Maria Cristina Napolitano, Giuseppe Scarpati, Gabriel Zuchtriegel, Alexandra Spühler, Michel E. Fuchs, Stuart James, Ohad Ben-Shahar, Marcello Pelillo, Alessio Del Bue:
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving. - Frederik Kunstner, Alan Milligan, Robin Yadav, Mark Schmidt, Alberto Bietti:
Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models. - Franziska Heeg, Ingo Scholtes:
Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs. - Yang Li, Jinpei Guo, Runzhong Wang, Hongyuan Zha, Junchi Yan:
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization. - Hai-Vy Nguyen, Fabrice Gamboa, Reda Chhaibi, Sixin Zhang, Serge Gratton, Thierry Giaccone:
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification. - Andrea Wynn, Ilia Sucholutsky, Tom Griffiths:
Learning Human-like Representations to Enable Learning Human Values. - Jin-Hong Du, Pratik Patil:
Implicit Regularization Paths of Weighted Neural Representations. - Min Zhao, Hongzhou Zhu, Chendong Xiang, Kaiwen Zheng, Chongxuan Li, Jun Zhu:
Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model. - Eunji Hong, Minh Hieu Nguyen, Mikaela Angelina Uy, Minhyuk Sung:
MV2Cyl: Reconstructing 3D Extrusion Cylinders from Multi-View Images. - Kwangho Kim, Jisu Kim, Larry A. Wasserman, Edward H. Kennedy:
Hierarchical and Density-based Causal Clustering. - Qisen Wang, Yifan Zhao, Jiawei Ma, Jia Li:
How to Use Diffusion Priors under Sparse Views? - Dar Gilboa, Hagay Michaeli, Daniel Soudry, Jarrod R. McClean:
Exponential Quantum Communication Advantage in Distributed Inference and Learning. - Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel:
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits. - Ido Sobol, Chenfeng Xu, Or Litany:
Zero-to-Hero: Enhancing Zero-Shot Novel View Synthesis via Attention Map Filtering. - Kendong Liu, Zhiyu Zhu, Chuanhao Li, Hui Liu, Huanqiang Zeng, Junhui Hou:
PrefPaint: Aligning Image Inpainting Diffusion Model with Human Preference. - Bikang Pan, Wei Huang, Ye Shi:
Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method. - Minyang Tian, Luyu Gao, Shizhuo Dylan Zhang, Xinan Chen, Cunwei Fan, Xuefei Guo, Roland Haas, Pan Ji, Kittithat Krongchon, Yao Li, Shengyan Liu, Di Luo, Yutao Ma, Hao Tong, Kha Trinh, Chenyu Tian, Zihan Wang, Bohao Wu, Shengzhu Yin, Minhui Zhu, Kilian Lieret, Yanxin Lu, Genglin Liu, Yufeng Du, Tianhua Tao, Ofir Press, Jamie Callan, Eliu A. Huerta, Hao Peng:
SciCode: A Research Coding Benchmark Curated by Scientists. - Zheng Chen, Haotong Qin, Yong Guo, Xiongfei Su, Xin Yuan, Linghe Kong, Yulun Zhang:
Binarized Diffusion Model for Image Super-Resolution. - Alejandro Lozano, Jeffrey J. Nirschl, James Burgess, Sanket Rajan Gupte, Yuhui Zhang, Alyssa Unell, Serena Yeung:
Micro-Bench: A Microscopy Benchmark for Vision-Language Understanding. - Zhengkai Lin, Zhihang Fu, Kai Liu, Liang Xie, Binbin Lin, Wenxiao Wang, Deng Cai, Yue Wu, Jieping Ye:
Delving into the Reversal Curse: How Far Can Large Language Models Generalize? - Xueyi Zhang, Mingrui Lao, Peng Zhao, Jun Tang, Yanming Guo, Siqi Cai, Xianghu Yue, Haizhou Li:
Language Without Borders: A Dataset and Benchmark for Code-Switching Lip Reading. - Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang:
On the Parameter Identifiability of Partially Observed Linear Causal Models. - Chau Tran, Duy M. H. Nguyen, Manh-Duy Nguyen, TrungTin Nguyen, Ngan Le, Pengtao Xie, Daniel Sonntag, James Y. Zou, Binh Nguyen, Mathias Niepert:
Accelerating Transformers with Spectrum-Preserving Token Merging. - Guilherme Penedo, Hynek Kydlícek, Loubna Ben Allal, Anton Lozhkov, Margaret Mitchell, Colin A. Raffel, Leandro von Werra, Thomas Wolf:
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale. - Qi Li, Xiang Liu, Zhenheng Tang, Peijie Dong, Zeyu Li, Xinglin Pan, Xiaowen Chu:
Should We Really Edit Language Models? On the Evaluation of Edited Language Models. - Stefan Stojanovic, Yassir Jedra, Alexandre Proutière:
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation. - Xin Xiao, Bohong Wu, Jiacong Wang, Chunyuan Li, Xun Zhou, Haoyuan Guo:
Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment. - Oswin So, Cheng Ge, Chuchu Fan:
Solving Minimum-Cost Reach Avoid using Reinforcement Learning. - Dongjoon Lee, Hyeryn Park, Changhee Lee:
Toward a Well-Calibrated Discrimination via Survival Outcome-Aware Contrastive Learning. - Luting Wang, Yang Zhao, Zijian Zhang, Jiashi Feng, Si Liu, Bingyi Kang:
Image Understanding Makes for A Good Tokenizer for Image Generation. - Hideaki Kim:
Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions. - Bowen Ping, Shuo Wang, Hanqing Wang, Xu Han, Yuzhuang Xu, Yukun Yan, Yun Chen, Baobao Chang, Zhiyuan Liu, Maosong Sun:
Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models. - Xilin He, Jingyu Hu, Qinliang Lin, Cheng Luo, Weicheng Xie, Siyang Song, Muhammad Haris Khan, Linlin Shen:
Towards Combating Frequency Simplicity-biased Learning for Domain Generalization. - Lili Wei, Congyan Lang, Ziyi Chen, Tao Wang, Yidong Li, Jun Liu:
Generated and Pseudo Content guided Prototype Refinement for Few-shot Point Cloud Segmentation. - Haoran He, Chenjia Bai, Ling Pan, Weinan Zhang, Bin Zhao, Xuelong Li:
Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training. - Andrew Jesson, Nicolas Beltran-Velez, Quentin Chu, Sweta Karlekar, Jannik Kossen, Yarin Gal, John P. Cunningham, David M. Blei:
Estimating the Hallucination Rate of Generative AI. - Vivian Y. Nastl, Moritz Hardt:
Do causal predictors generalize better to new domains? - Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob R. Gardner, Geoff Pleiss, John P. Cunningham:
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference. - Weiwei Ye, Songgaojun Deng, Qiaosha Zou, Ning Gui:
Frequency Adaptive Normalization For Non-stationary Time Series Forecasting. - Giovanni De Toni, Nastaran Okati, Suhas Thejaswi, Eleni Straitouri, Manuel Rodriguez:
Towards Human-AI Complementarity with Prediction Sets. - Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, Stuart J. Russell:
Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. - Wenhao Yang, Yibo Wang, Peng Zhao, Lijun Zhang:
Universal Online Convex Optimization with 1 Projection per Round. - Maor Ashkenazi, Eran Treister:
Towards Croppable Implicit Neural Representations. - Jinhee Kim, Taesung Kim, Jaegul Choo:
EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models. - Suzanne Duncan, Gianna Leoni, Lee Steven, Keoni Mahelona, Peter-Lucas Jones:
Fit for our purpose, not yours: Benchmark for a low-resource, Indigenous language. - Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li, Sophia Pi, Zhao Song, Han Liu:
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs). - Zhixiang Shen, Shuo Wang, Zhao Kang:
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning. - Andrew Wagenmaker, Lu Mi, Marton Rozsa, Matthew S. Bull, Karel Svoboda, Kayvon Daie, Matthew D. Golub, Kevin G. Jamieson:
Active learning of neural population dynamics using two-photon holographic optogenetics. - Sheng Yan, Cunhang Fan, Hongyu Zhang, Xiaoke Yang, Jianhua Tao, Zhao Lv:
DARNet: Dual Attention Refinement Network with Spatiotemporal Construction for Auditory Attention Detection. - Yiling Xie, Xiaoming Huo:
High-dimensional (Group) Adversarial Training in Linear Regression. - Yuefei Lyu, Chaozhuo Li, Sihong Xie, Xi Zhang:
Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning. - Arlind Kadra, Sebastian Pineda-Arango, Josif Grabocka:
Interpretable Mesomorphic Networks for Tabular Data. - Aviv Bick, Kevin Y. Li, Eric P. Xing, J. Zico Kolter, Albert Gu:
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. - Muhammad Umair Nasir, Steven James, Julian Togelius:
GameTraversalBenchmark: Evaluating Planning Abilities Of Large Language Models Through Traversing 2D Game Maps. - Yi-Kai Zhang, Shiyin Lu, Yang Li, Yanqing Ma, Qingguo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, De-Chuan Zhan, Han-Jia Ye:
Wings: Learning Multimodal LLMs without Text-only Forgetting. - Rahul Saxena, Taeyoun Kim, Aman Mehra, Christina Baek, J. Zico Kolter, Aditi Raghunathan:
Predicting the Performance of Foundation Models via Agreement-on-the-Line. - Christian Holberg, Cristopher Salvi:
Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals. - Philipp Schleich, Marta Skreta, Lasse Bjørn Kristensen, Rodrigo A. Vargas-Hernández, Alán Aspuru-Guzik:
Quantum Deep Equilibrium Models. - Xinyi Yu, Haonan Jiang, Li Zhang, Lin Yuanbo Wu, Linlin Ou, Liu Liu:
EfficientCAPER: An End-to-End Framework for Fast and Robust Category-Level Articulated Object Pose Estimation. - Tong Wu, Yinghao Xu, Ryan Po, Mengchen Zhang, Guandao Yang, Jiaqi Wang, Ziwei Liu, Dahua Lin, Gordon Wetzstein:
FiVA: Fine-grained Visual Attribute Dataset for Text-to-Image Diffusion Models. - Jialiang Wang, Xiong Zhou, Deming Zhai, Junjun Jiang, Xiangyang Ji, Xianming Liu:
$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise. - Sihan Liu, Christopher Ye:
Replicable Uniformity Testing. - Ye Liu, Zongyang Ma, Zhongang Qi, Yang Wu, Ying Shan, Chang Wen Chen:
E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding. - Ce Zhang, Simon Stepputtis, Katia P. Sycara, Yaqi Xie:
Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models. - Han Huang, Elchanan Mossel:
Low Degree Hardness for Broadcasting on Trees. - Zhao Xu, Fan Liu, Hao Liu:
Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. - Gaia Molinaro, Cédric Colas, Pierre-Yves Oudeyer, Anne Collins:
Latent Learning Progress Drives Autonomous Goal Selection in Human Reinforcement Learning. - Miguel Á. Carreira-Perpiñán, Kuat Gazizov:
The tree autoencoder model, with application to hierarchical data visualization. - Nima Dehmamy, Csaba Both, Jeet Mohapatra, Subhro Das, Tommi Jaakkola:
Neural Network Reparametrization for Accelerated Optimization in Molecular Simulations. - Jakob Hauser, Dániel Kondor, Jenny Reddish, Majid Benam, Enrico Cioni, Federica Villa, James Bennett, Daniel Hoyer, Pieter Francois, Peter Turchin, R. Maria del Rio Chanona:
Large Language Models' Expert-level Global History Knowledge Benchmark (HiST-LLM). - Yunshu Wu, Yingtao Luo, Xianghao Kong, Vagelis Papalexakis, Greg Ver Steeg:
Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training. - Zhiyi Pan, Wei Gao, Shan Liu, Ge Li:
Distribution Guidance Network for Weakly Supervised Point Cloud Semantic Segmentation. - Skyler Wu, Fred Lu, Edward Raff, James Holt:
Stabilizing Linear Passive-Aggressive Online Learning with Weighted Reservoir Sampling. - Zhoutong Wu, Yimu Zhang, Cong Fang, Zhouchen Lin:
Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics. - Lucas Laird, Circe Hsu, Asilata Bapat, Robin Walters:
MatrixNet: Learning over symmetry groups using learned group representations. - Anna Korba, Francis R. Bach, Clémentine Chazal:
Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence. - Xiaoxiao Ma, Zhixiang Wei, Yi Jin, Pengyang Ling, Tianle Liu, Ben Wang, Junkang Dai, Huaian Chen:
Masked Pre-training Enables Universal Zero-shot Denoiser. - Hanwei Zhu, Haoning Wu, Yixuan Li, Zicheng Zhang, Baoliang Chen, Lingyu Zhu, Yuming Fang, Guangtao Zhai, Weisi Lin, Shiqi Wang:
Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare. - Hanshi Sun, Momin Haider, Ruiqi Zhang, Huitao Yang, Jiahao Qiu, Ming Yin, Mengdi Wang, Peter L. Bartlett, Andrea Zanette:
Fast Best-of-N Decoding via Speculative Rejection. - Dingkang Liang, Xin Zhou, Wei Xu, Xingkui Zhu, Zhikang Zou, Xiaoqing Ye, Xiao Tan, Xiang Bai:
PointMamba: A Simple State Space Model for Point Cloud Analysis. - Dombry Clement, Ahmed Zaoui:
Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation. - Yuanqing Wang, Kyunghyun Cho:
Non-convolutional graph neural networks. - Maitreya Patel, Abhiram Kusumba, Sheng Cheng, Changhoon Kim, Tejas Gokhale, Chitta Baral, Yezhou Yang:
TripletCLIP: Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives. - Suzanna Sia, David Mueller, Kevin Duh:
Where does In-context Learning Happen in Large Language Models? - Tianshi Wang, Qikai Yang, Ruijie Wang, Dachun Sun, Jinyang Li, Yizhuo Chen, Yigong Hu, Chaoqi Yang, Tomoyoshi Kimura, Denizhan Kara, Tarek F. Abdelzaher:
Fine-grained Control of Generative Data Augmentation in IoT Sensing. - Yiwei Wu, Leah Ajmani, Shayne Longpre, Hanlin Li:
A Systematic Review of NeurIPS Dataset Management Practices. - Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann:
Geodesic Optimization for Predictive Shift Adaptation on EEG data. - Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Jing Jiang, Min Lin:
Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses. - Michael Luo, Justin Wong, Brandon Trabucco, Yanping Huang, Joseph E. Gonzalez, Zhifeng Chen, Ruslan Salakhutdinov, Ion Stoica:
Stylus: Automatic Adapter Selection for Diffusion Models. - Moritz Schneider, Robert Krug, Narunas Vaskevicius, Luigi Palmieri, Joschka Boedecker:
The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning. - Hao Phung, Quan Dao, Trung Tuan Dao, Viet Hoang Phan, Dimitris N. Metaxas, Anh Tuan Tran:
DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation. - Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori B. Hashimoto:
Graph-based Uncertainty Metrics for Long-form Language Model Generations. - Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose:
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation. - Xiufeng Huang, Ruiqi Li, Yiu-ming Cheung, Ka Chun Cheung, Simon See, Renjie Wan:
GaussianMarker: Uncertainty-Aware Copyright Protection of 3D Gaussian Splatting. - Sami Davies, Sergei Vassilvitskii, Yuyan Wang:
Warm-starting Push-Relabel. - Tian Wang, Chuang Wang:
Latent Neural Operator for Solving Forward and Inverse PDE Problems. - Huanjin Yao, Wenhao Wu, Taojiannan Yang, Yuxin Song, Mengxi Zhang, Haocheng Feng, Yifan Sun, Zhiheng Li, Wanli Ouyang, Jingdong Wang:
Dense Connector for MLLMs. - Hiroshi Kera, Yuki Ishihara, Yuta Kambe, Tristan Vaccon, Kazuhiro Yokoyama:
Learning to compute Gröbner bases. - Shuxia Lin, Miaosen Zhang, Ruiming Chen, Xu Yang, Qiufeng Wang, Xin Geng:
Linearly Decomposing and Recomposing Vision Transformers for Diverse-Scale Models. - Woochul Kang, Hyungseop Lee:
Adaptive Depth Networks with Skippable Sub-Paths. - Anqi Zhang, Guangyu Gao, Jianbo Jiao, Chi Liu, Yunchao Wei:
Bridge the Points: Graph-based Few-shot Segment Anything Semantically. - Weiting Tan, Jingyu Zhang, Lingfeng Shen, Daniel Khashabi, Philipp Koehn:
DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation. - Sebastian Zeng, Florian Graf, Martin Uray, Stefan Huber, Roland Kwitt:
Neural Persistence Dynamics. - Zongjiang Shang, Ling Chen, Binqing Wu, Dongliang Cui:
Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting. - Xiong Peng, Bo Han, Feng Liu, Tongliang Liu, Mingyuan Zhou:
Pseudo-Private Data Guided Model Inversion Attacks. - Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin:
Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention. - Kevin Wu, Eric Wu, James Y. Zou:
ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence. - Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju:
MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models. - Matthew Zurek, Yudong Chen:
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs. - Bhavika Devnani, Skyler Seto, Zakaria Aldeneh, Alessandro Toso, Elena Menyaylenko, Barry-John Theobald, Jonathan Sheaffer, Miguel Sarabia:
Learning Spatially-Aware Language and Audio Embeddings. - Shivvrat Arya, Tahrima Rahman, Vibhav Gogate:
A Neural Network Approach for Efficiently Answering Most Probable Explanation Queries in Probabilistic Models. - Jiaojiao Fan, Haotian Xue, Qinsheng Zhang, Yongxin Chen:
RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance. - Dobrik Georgiev, Joseph Wilson, Davide Buffelli, Pietro Lió:
Deep Equilibrium Algorithmic Reasoning. - Aditi Jha, Diksha Gupta, Carlos D. Brody, Jonathan W. Pillow:
Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems. - Yang Qian, Xinbiao Wang, Yuxuan Du, Yong Luo, Dacheng Tao:
MG-Net: Learn to Customize QAOA with Circuit Depth Awareness. - Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao:
Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks. - Yuezhou Hu, Jun Zhu, Jianfei Chen:
S-STE: Continuous Pruning Function for Efficient 2: 4 Sparse Pre-training. - David McAllister, Songwei Ge, Jia-Bin Huang, David Jacobs, Alexei A. Efros, Aleksander Holynski, Angjoo Kanazawa:
Rethinking Score Distillation as a Bridge Between Image Distributions. - Amber Hu, David M. Zoltowski, Aditya Nair, David Anderson, Lea Duncker, Scott W. Linderman:
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems. - Nolan Dey, Shane Bergsma, Joel Hestness:
Sparse maximal update parameterization: A holistic approach to sparse training dynamics. - Haoyue Bai, Jifan Zhang, Robert D. Nowak:
AHA: Human-Assisted Out-of-Distribution Generalization and Detection. - Wei Jiang, Sifan Yang, Wenhao Yang, Lijun Zhang:
Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction. - Zichen Jeff Cui, Hengkai Pan, Aadhithya Iyer, Siddhant Haldar, Lerrel Pinto:
DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control. - Marc Wanner, Laura Lewis, Chiranjib Bhattacharyya, Devdatt P. Dubhashi, Alexandru Gheorghiu:
Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms. - Li Sun, Zhenhao Huang, Qiqi Wan, Hao Peng, Philip S. Yu:
Spiking Graph Neural Network on Riemannian Manifolds. - Li Jiao, Qiuxia Lai, Yu Li, Qiang Xu:
Vector Quantization Prompting for Continual Learning. - Julen Etxaniz, Gorka Azkune, Aitor Soroa, Oier Lopez de Lacalle, Mikel Artetxe:
BertaQA: How Much Do Language Models Know About Local Culture? - Matthew Zheng, Enis Simsar, Hidir Yesiltepe, Federico Tombari, Joel Simon, Pinar Yanardag Delul:
Stylebreeder: Exploring and Democratizing Artistic Styles through Text-to-Image Models. - Mengxiao Zhang, Haipeng Luo:
Contextual Multinomial Logit Bandits with General Value Functions. - Zixian Huang, Wenhao Zhu, Gong Cheng, Lei Li, Fei Yuan:
MindMerger: Efficiently Boosting LLM Reasoning in non-English Languages. - Gaurang Sriramanan, Siddhant Bharti, Vinu Sankar Sadasivan, Shoumik Saha, Priyatham Kattakinda, Soheil Feizi:
LLM-Check: Investigating Detection of Hallucinations in Large Language Models. - David Lipshutz, Eero P. Simoncelli:
Shaping the distribution of neural responses with interneurons in a recurrent circuit model. - Haobo Zhang, Xiyue Peng, Honghao Wei, Xin Liu:
Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage. - Allen Roush, Yusuf Shabazz, Arvind Balaji, Peter Zhang, Stefano Mezza, Markus Zhang, Sanjay Basu, Sriram Vishwanath, Ravid Shwartz-Ziv:
OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset. - Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael D. Riley, Sanjiv Kumar, Adrian Benton:
Accelerating Blockwise Parallel Language Models with Draft Refinement. - Jianzong Wu, Xiangtai Li, Yanhong Zeng, Jiangning Zhang, Qianyu Zhou, Yining Li, Yunhai Tong, Kai Chen:
MotionBooth: Motion-Aware Customized Text-to-Video Generation. - Seungwoo Yoo, Juil Koo, Kyeongmin Yeo, Minhyuk Sung:
Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses. - Dominik Fuchsgruber, Tom Wollschläger, Stephan Günnemann:
Energy-based Epistemic Uncertainty for Graph Neural Networks. - Chao Yi, Yuhang He, De-Chuan Zhan, Han-Jia Ye:
Bridge the Modality and Capability Gaps in Vision-Language Model Selection. - Kailai Yang, Zhiwei Liu, Qianqian Xie, Jimin Huang, Tianlin Zhang, Sophia Ananiadou:
MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models. - Yu Chen, Gim Hee Lee:
DOGS: Distributed-Oriented Gaussian Splatting for Large-Scale 3D Reconstruction Via Gaussian Consensus. - Hamadi Chihaoui, Abdelhak Lemkhenter, Paolo Favaro:
Blind Image Restoration via Fast Diffusion Inversion. - Mathilde Caron, Alireza Fathi, Cordelia Schmid, Ahmet Iscen:
Web-Scale Visual Entity Recognition: An LLM-Driven Data Approach. - Zihan Tan, Guancheng Wan, Wenke Huang, Mang Ye:
FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference. - Felix Dangel, Johannes Müller, Marius Zeinhofer:
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks. - Yiqi Zhang, Yang You:
SpeedLoader: An I/O efficient scheme for heterogeneous and distributed LLM operation. - Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov:
CoSy: Evaluating Textual Explanations of Neurons. - Xinran Nicole Han, Todd E. Zickler, Ko Nishino:
Multistable Shape from Shading Emerges from Patch Diffusion. - Yule Wang, Chengrui Li, Weihan Li, Anqi Wu:
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models. - Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, Daria Gitman, Fei Jia, Igor Gitman:
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset. - Avi Caciularu, Alon Jacovi, Eyal Ben-David, Sasha Goldshtein, Tal Schuster, Jonathan Herzig, Gal Elidan, Amir Globerson:
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools. - Jiewen Yang, Yiqun Lin, Bin Pu, Xiaomeng Li:
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding. - Konstantinos Kogkalidis, Jean-Philippe Bernardy, Vikas Garg:
Algebraic Positional Encodings. - Daniel Hothem, Ashe Miller, Timothy Proctor:
What is my quantum computer good for? Quantum capability learning with physics-aware neural networks. - Anna Mészáros, Szilvia Ujváry, Wieland Brendel, Patrik Reizinger, Ferenc Huszar:
Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts. - Grigory Malinovsky, Peter Richtárik, Samuel Horváth, Eduard Gorbunov:
Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences. - Ye Li, Lingdong Kong, Hanjiang Hu, Xiaohao Xu, Xiaonan Huang:
Is Your LiDAR Placement Optimized for 3D Scene Understanding? - Baohao Liao, Christof Monz:
3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability. - Han Wang, Sharon Li:
Bridging OOD Detection and Generalization: A Graph-Theoretic View. - Xing Cui, Peipei Li, Zekun Li, Xuannan Liu, Yueying Zou, Zhaofeng He:
Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner. - Rui Hu, Qian He, Gaofeng He, Jiedong Zhuang, Huang Chen, Huafeng Liu, Huamin Wang:
FashionR2R: Texture-preserving Rendered-to-Real Image Translation with Diffusion Models. - Minu Kim, Yongsik Lee, Sehyeok Kang, Jihwan Oh, Song Chong, Se-Young Yun:
Preference Alignment with Flow Matching. - Guillaume Wang, Alireza Mousavi Hosseini, Lénaïc Chizat:
Mean-Field Langevin Dynamics for Signed Measures via a Bilevel Approach. - Niloufar Zakariaei, Siddharth Rout, Eldad Haber, Moshe Eliasof:
Advection Augmented Convolutional Neural Networks. - Darshan Chakrabarti, Julien Grand-Clément, Christian Kroer:
Extensive-Form Game Solving via Blackwell Approachability on Treeplexes. - Chengchang Liu, Chaowen Guan, Jianhao He, John C. S. Lui:
Quantum Algorithms for Non-smooth Non-convex Optimization. - Jose H. Blanchet, Jiajin Li, Markus Pelger, Greg Zanotti:
Automatic Outlier Rectification via Optimal Transport. - Marco Nurisso, Pierrick Leroy, Francesco Vaccarino:
Topological obstruction to the training of shallow ReLU neural networks. - Yizhe Huang, Xingbo Wang, Hao Liu, Fanqi Kong, Aoyang Qin, Min Tang, Xiaoxi Wang, Song-Chun Zhu, Mingjie Bi, Siyuan Qi, Xue Feng:
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making. - Jiaqi Li, Qianshan Wei, Chuanyi Zhang, Guilin Qi, Miaozeng Du, Yongrui Chen, Sheng Bi, Fan Liu:
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models. - Sizhe Liu, Jun Xia, Lecheng Zhang, Yuchen Liu, Yue Liu, Wenjie Du, Zhangyang Gao, Bozhen Hu, Cheng Tan, Hongxin Xiang, Stan Z. Li:
FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning. - Kezheng Xiong, Haoen Xiang, Qingshan Xu, Chenglu Wen, Siqi Shen, Jonathan Jun Li, Cheng Wang:
Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration. - Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Improving robustness to corruptions with multiplicative weight perturbations. - Nan Jiang, Xiaopeng Li, Shiqi Wang, Qiang Zhou, Soneya Binta Hossain, Baishakhi Ray, Varun Kumar, Xiaofei Ma, Anoop Deoras:
LeDex: Training LLMs to Better Self-Debug and Explain Code. - Evan Markou, Thalaiyasingam Ajanthan, Stephen Gould:
Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame. - Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson:
Time-Constrained Robust MDPs. - Zhonglin Sun, Siyang Song, Ioannis Patras, Georgios Tzimiropoulos:
CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition. - Eric Balkanski, Vasilis Gkatzelis, Golnoosh Shahkarami:
Randomized Strategic Facility Location with Predictions. - Owen Dugan, Donato Jiménez-Benetó, Charlotte Loh, Zhuo Chen, Rumen Dangovski, Marin Soljacic:
OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step. - Mingchen Li, Yang Tan, Xinzhu Ma, Bozitao Zhong, Huiqun Yu, Ziyi Zhou, Wanli Ouyang, Bingxin Zhou, Pan Tan, Liang Hong:
ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention. - Haoyuan Qin, Chennan Ma, Mian Deng, Zhengzhu Liu, Songzhu Mei, Xinwang Liu, Cheng Wang, Siqi Shen:
The Dormant Neuron Phenomenon in Multi-Agent Reinforcement Learning Value Factorization. - Hexuan Deng, Wenxiang Jiao, Xuebo Liu, Min Zhang, Zhaopeng Tu:
NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updates. - Jiawen Chen, Muqing Zhou, Wenrong Wu, Jinwei Zhang, Yun Li, Didong Li:
STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics. - Blake Bordelon, Hamza Tahir Chaudhry, Cengiz Pehlevan:
Infinite Limits of Multi-head Transformer Dynamics. - Maximilian Granz, Manuel Heurich, Tim Landgraf:
WeiPer: OOD Detection using Weight Perturbations of Class Projections. - Guhan Chen, Yicheng Li, Qian Lin:
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory. - Han Lu, Yichen Xie, Xiaokang Yang, Junchi Yan:
Boundary Matters: A Bi-Level Active Finetuning Method. - Natasa Tagasovska, Vladimir Gligorijevic, Kyunghyun Cho, Andreas Loukas:
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient. - Satwik Bhattamishra, Michael Hahn, Phil Blunsom, Varun Kanade:
Separations in the Representational Capabilities of Transformers and Recurrent Architectures. - Tim Salimans, Thomas Mensink, Jonathan Heek, Emiel Hoogeboom:
Multistep Distillation of Diffusion Models via Moment Matching. - Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara:
AUC Maximization under Positive Distribution Shift. - Ting-Hsuan Chen, Jiewen Chan, Hau-Shiang Shiu, Shih-Han Yen, Changhan Yeh, Yu-Lun Liu:
NaRCan: Natural Refined Canonical Image with Integration of Diffusion Prior for Video Editing. - Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel:
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. - Xingyu Xu, Yuejie Chi:
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction. - Letian Gong, Yan Lin, Xinyue Zhang, Yiwen Lu, Xuedi Han, Yichen Liu, Shengnan Guo, Youfang Lin, Huaiyu Wan:
Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models. - Mengxi Chen, Fei Zhang, Zihua Zhao, Jiangchao Yao, Ya Zhang, Yanfeng Wang:
Probabilistic Conformal Distillation for Enhancing Missing Modality Robustness. - Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge:
Causal discovery with endogenous context variables. - Zahra Gharaee, Scott C. Lowe, ZeMing Gong, Pablo Millan Arias, Nicholas Pellegrino, Austin T. Wang, Joakim Bruslund Haurum, Iuliia Eyriay, Lila Kari, Dirk Steinke, Graham W. Taylor, Paul W. Fieguth, Angel X. Chang:
BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity. - Yihe Wang, Nan Huang, Taida Li, Yujun Yan, Xiang Zhang:
Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification. - Hugo Cui, Freya Behrens, Florent Krzakala, Lenka Zdeborová:
A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention. - Nathaniel Weir, Muhammad Khalifa, Linlu Qiu, Orion Weller, Peter Clark:
Learning to Reason via Program Generation, Emulation, and Search. - Abhineet Agarwal, Anish Agarwal, Lorenzo Masoero, Justin Whitehouse:
Mutli-Armed Bandits with Network Interference. - Nicola Bariletto, Nhat Ho:
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization. - Hao-Yi Lei, Zhi-Hao Tan, Zhi-Hua Zhou:
On the Ability of Developers' Training Data Preservation of Learnware. - Qinwei Yang, Xueqing Liu, Yan Zeng, Ruocheng Guo, Yang Liu, Peng Wu:
Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards. - Luke Marks, Amir Abdullah, Clement Neo, Rauno Arike, David Krueger, Philip Torr, Fazl Barez:
Interpreting Learned Feedback Patterns in Large Language Models. - Xin Wen, Bingchen Zhao, Yilun Chen, Jiangmiao Pang, Xiaojuan Qi:
What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights. - Hamish Ivison, Yizhong Wang, Jiacheng Liu, Zeqiu Wu, Valentina Pyatkin, Nathan Lambert, Noah A. Smith, Yejin Choi, Hanna Hajishirzi:
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback. - Kedar Karhadkar, Erin George, Michael Murray, Guido F. Montúfar, Deanna Needell:
Benign overfitting in leaky ReLU networks with moderate input dimension. - Saptarshi Roy, Zehua Wang, Ambuj Tewari:
On the Computational Complexity of Private High-dimensional Model Selection. - Weiyu Guo, Ying Sun, Yijie Xu, Ziyue Qiao, Yongkui Yang, Hui Xiong:
SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network. - Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu:
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. - Zinan Guo, Yanze Wu, Zhuowei Chen, Lang Chen, Peng Zhang, Qian He:
PuLID: Pure and Lightning ID Customization via Contrastive Alignment. - Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Guha, Sheng Shen, Mohamed Awadalla, Silvio Savarese, Caiming Xiong, Ran Xu, Yejin Choi, Ludwig Schmidt:
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens. - Manuel Brenner, Christoph Jürgen Hemmer, Zahra Monfared, Daniel Durstewitz:
Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction. - Kuzma Khrabrov, Anton Ber, Artem Tsypin, Konstantin Ushenin, Egor Rumiantsev, Alexander Telepov, Dmitry Protasov, Ilya Shenbin, Anton Alekseev, Mikhail Shirokikh, Sergey I. Nikolenko, Elena Tutubalina, Artur Kadurin:
$\nabla^2$DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials. - Ruoxue Liu, Linjiajie Fang, Wenjia Wang, Bingyi Jing:
D2R2: Diffusion-based Representation with Random Distance Matching for Tabular Few-shot Learning. - Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen, Ahmed Salem, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramèr, Sahar Abdelnabi, Lea Schönherr:
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. - Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang:
Learning Discrete Concepts in Latent Hierarchical Models. - Nidhish Shah, Zulkuf Genc, Dogu Araci:
StackEval: Benchmarking LLMs in Coding Assistance. - Jinrui Yang, Xianhang Li, Druv Pai, Yuyin Zhou, Yi Ma, Yaodong Yu, Cihang Xie:
Scaling White-Box Transformers for Vision. - Xinyue Chen, Yazhou Ren, Jie Xu, Fangfei Lin, Xiaorong Pu, Yang Yang:
Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views. - Weixin An, Yuanyuan Liu, Fanhua Shang, Hongying Liu:
Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications. - Jin Zhang, Ze Liu, Defu Lian, Enhong Chen:
Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure. - Shyam Sundhar Ramesh, Yifan Hu, Iason Chaimalas, Viraj Mehta, Pier Giuseppe Sessa, Haitham Bou-Ammar, Ilija Bogunovic:
Group Robust Preference Optimization in Reward-free RLHF. - Jin-Hwa Kim:
Polyhedral Complex Derivation from Piecewise Trilinear Networks. - Connor Clayton, Jiaqi Leng, Gengzhi Yang, Yi-Ling Qiao, Ming C. Lin, Xiaodi Wu:
Differentiable Quantum Computing for Large-scale Linear Control. - Jun Dan, Yang Liu, Jiankang Deng, Haoyu Xie, Siyuan Li, Baigui Sun, Shan Luo:
TopoFR: A Closer Look at Topology Alignment on Face Recognition. - François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni:
Fair Online Bilateral Trade. - Zhaoxian Wu, Tayfun Gokmen, Malte J. Rasch, Tianyi Chen:
Towards Exact Gradient-based Training on Analog In-memory Computing. - Krzysztof Marcin Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Kumar Avinava Dubey, Tamás Sarlós, Snigdha Chaturvedi:
Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers. - Romain Cosson, Laurent Massoulié:
Barely Random Algorithms and Collective Metrical Task Systems. - Lingkai Kong, Haorui Wang, Wenhao Mu, Yuanqi Du, Yuchen Zhuang, Yifei Zhou, Yue Song, Rongzhi Zhang, Kai Wang, Chao Zhang:
Aligning Large Language Models with Representation Editing: A Control Perspective. - Xinbo Ai:
Adjust Pearson's $r$ to Measure Arbitrary Monotone Dependence. - Jiayu Su, David A. Knowles, Raúl Rabadán:
Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis. - Maximilien Dreveton, Charbel Chucri, Matthias Grossglauser, Patrick Thiran:
Why the Metric Backbone Preserves Community Structure. - Jiaming Zhuo, Yintong Lu, Hui Ning, Kun Fu, Bingxin Niu, Dongxiao He, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang:
Unified Graph Augmentations for Generalized Contrastive Learning on Graphs. - Bo Chen, Zhilei Bei, Xingyi Cheng, Pan Li, Jie Tang, Le Song:
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training. - Junsheng Zhou, Weiqi Zhang, Yu-Shen Liu:
DiffGS: Functional Gaussian Splatting Diffusion. - Baoyu Jing, Shuqi Gu, Tianyu Chen, Zhiyu Yang, Dongsheng Li, Jingrui He, Kan Ren:
Towards Editing Time Series. - Xiang Meng, Kayhan Behdin, Haoyue Wang, Rahul Mazumder:
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models. - Mohammad Pedramfar, Vaneet Aggarwal:
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization. - Liyi Chen, Panrong Tong, Zhongming Jin, Ying Sun, Jieping Ye, Hui Xiong:
Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs. - Andrea Schioppa:
Efficient Sketches for Training Data Attribution and Studying the Loss Landscape. - Xiao Liu, Muyang Lyu, Cong Yu, Si Wu:
To Learn or Not to Learn, That is the Question - A Feature-Task Dual Learning Model of Perceptual Learning. - Peiyao Wang, Yuewei Lin, Erik Blasch, Jie Wei, Haibin Ling:
Efficient Temporal Action Segmentation via Boundary-aware Query Voting. - Thang Duong, Zhi Wang, Chicheng Zhang:
Beyond task diversity: provable representation transfer for sequential multitask linear bandits. - Neil Ashton, Jordan B. Angel, Aditya S. Ghate, Gaetan K. W. Kenway, Man Long Wong, Cetin C. Kiris, Astrid Walle, Danielle C. Maddix, Gary Page:
WindsorML: High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics. - Zhaoze Wang, Ronald W. Di Tullio, Spencer Rooke, Vijay Balasubramanian:
Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences. - Yan-Feng Xie, Peng Zhao, Zhi-Hua Zhou:
Gradient-Variation Online Learning under Generalized Smoothness. - Qingyun Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S. Yu:
GC-Bench: An Open and Unified Benchmark for Graph Condensation. - Yiqian Zhang, Buyu Liu, Jun Bao, Qiang Huang, Min Zhang, Jun Yu:
Learnability Matters: Active Learning for Video Captioning. - Matthew J. Holland, Kosuke Nakatani:
Soft ascent-descent as a stable and flexible alternative to flooding. - Ameya Prabhu, Shiven Sinha, Ponnurangam Kumaraguru, Philip Torr, Ozan Sener, Puneet K. Dokania:
RanDumb: Random Representations Outperform Online Continually Learned Representations. - Gagan Aggarwal, Anupam Gupta, Andrés Perlroth, Grigoris Velegkas:
Randomized Truthful Auctions with Learning Agents. - Benno Krojer, Dheeraj Vattikonda, Luis Lara, Varun Jampani, Eva Portelance, Chris Pal, Siva Reddy:
Learning Action and Reasoning-Centric Image Editing from Videos and Simulation. - Hansol Lee, Tackgeun You, Hansoo Park, Woohyeon Shim, Sanghyeon Kim, Hwasup Lim:
ContactField: Implicit Field Representation for Multi-Person Interaction Geometry. - Nikolaos-Ioannis Bountos, Maria Sdraka, Angelos Zavras, Andreas Karavias, Ilektra Karasante, Themistocles Herekakis, Angeliki Thanasou, Dimitrios Michail, Ioannis Papoutsis:
Kuro Siwo: 33 billion m2 under the water. A global multi-temporal satellite dataset for rapid flood mapping. - Haoxiang Ma, Modi Shi, Boyang Gao, Di Huang:
Active Perception for Grasp Detection via Neural Graspness Field. - Zhonghao Wang, Danyu Sun, Sheng Zhou, Haobo Wang, Jiapei Fan, Longtao Huang, Jiajun Bu:
NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise. - Xinnuo Xu, Minyoung Kim, Royson Lee, Brais Martínez, Timothy M. Hospedales:
A Bayesian Approach to Data Point Selection. - Huidong Liang, Xingchen Wan, Xiaowen Dong:
Bayesian Optimization of Functions over Node Subsets in Graphs. - Sanjay Haresh, Daniel Dijkman, Apratim Bhattacharyya, Roland Memisevic:
ClevrSkills: Compositional Language And Visual Reasoning in Robotics. - Jingtong Su, Julia Kempe, Karen Ullrich:
Mission Impossible: A Statistical Perspective on Jailbreaking LLMs. - Hamidreza Kamkari, Brendan Leigh Ross, Rasa Hosseinzadeh, Jesse C. Cresswell, Gabriel Loaiza-Ganem:
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models. - Tankred Saanum, Peter Dayan, Eric Schulz:
Simplifying Latent Dynamics with Softly State-Invariant World Models. - Dutch Hansen, Siddartha Devic, Preetum Nakkiran, Vatsal Sharan:
When is Multicalibration Post-Processing Necessary? - Steven Li, Rickmer Krohn, Tao Chen, Anurag Ajay, Pulkit Agrawal, Georgia Chalvatzaki:
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient. - Lijun Zhang, Xiao Liu, Antoni Viros Martin, Cindy Xiong Bearfield, Yuriy Brun, Hui Guan:
Attack-Resilient Image Watermarking Using Stable Diffusion. - Miso Lee, Jihwan Kim, Jae-Pil Heo:
Activating Self-Attention for Multi-Scene Absolute Pose Regression. - Jialu Li, Jaemin Cho, Yi-Lin Sung, Jaehong Yoon, Mohit Bansal:
SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data. - Zaixi Zhang, Marinka Zitnik, Qi Liu:
Generalized Protein Pocket Generation with Prior-Informed Flow Matching. - Kai Yan, Alexander G. Schwing, Yu-Xiong Wang:
Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers. - Yi Ren, Shangmin Guo, Linlu Qiu, Bailin Wang, Danica J. Sutherland:
Bias Amplification in Language Model Evolution: An Iterated Learning Perspective. - Michele Caprio, Maryam Sultana, Eleni Elia, Fabio Cuzzolin:
Credal Learning Theory. - Qian Li, Tian Ding, Linxin Yang, Minghui Ouyang, Qingjiang Shi, Ruoyu Sun:
On the Power of Small-size Graph Neural Networks for Linear Programming. - Hugo Malard, Michel Olvera, Stéphane Lathuilière, Slim Essid:
An eye for an ear: zero-shot audio description leveraging an image captioner with audio-visual token distribution matching. - Yabin Zhang, Lei Zhang:
AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Models. - Angelos Assos, Yuval Dagan, Constantinos Daskalakis:
Maximizing utility in multi-agent environments by anticipating the behavior of other learners. - Sherry Yang, Simon L. Batzner, Ruiqi Gao, Muratahan Aykol, Alexander L. Gaunt, Brendan McMorrow, Danilo Jimenez Rezende, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk:
Generative Hierarchical Materials Search. - Xinhao Yao, Xiaolin Hu, Shenzhi Yang, Yong Liu:
Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective. - Eli Chien, Haoyu Wang, Ziang Chen, Pan Li:
Certified Machine Unlearning via Noisy Stochastic Gradient Descent. - Moritz Haas, Jin Xu, Volkan Cevher, Leena Chennuru Vankadara:
μP2: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling. - Sadegh Mahdavi, Raquel Aoki, Keyi Tang, Yanshuai Cao:
Leveraging Environment Interaction for Automated PDDL Translation and Planning with Large Language Models. - Xingyu Zheng, Xianglong Liu, Yichen Bian, Xudong Ma, Yulun Zhang, Jiakai Wang, Jinyang Guo, Haotong Qin:
BiDM: Pushing the Limit of Quantization for Diffusion Models. - Hamidreza Hashempoorikderi, Wan Choi:
Gated Inference Network: Inference and Learning State-Space Models. - Evelyn Ma, Chao Pan, S. Rasoul Etesami, Han Zhao, Olgica Milenkovic:
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning. - Junsheng Zhou, Yu-Shen Liu, Zhizhong Han:
Zero-Shot Scene Reconstruction from Single Images with Deep Prior Assembly. - Christopher J. Kymn, Sonia Mazelet, Anthony Thomas, Denis Kleyko, Edward Paxon Frady, Fritz Sommer, Bruno A. Olshausen:
Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps. - Zaitang Li, Pin-Yu Chen, Tsung-Yi Ho:
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models. - Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Youssef Mroueh:
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking. - Yanan Zhang, Jiangmeng Li, Lixiang Liu, Wenwen Qiang:
Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective. - Guangyu Wang, Wenchao Liu, Yuhong He, Cong Xu, Lin Ma, Haifeng Li:
EEGPT: Pretrained Transformer for Universal and Reliable Representation of EEG Signals. - Zhongpai Gao, Benjamin Planche, Meng Zheng, Xiao Chen, Terrence Chen, Ziyan Wu:
DDGS-CT: Direction-Disentangled Gaussian Splatting for Realistic Volume Rendering. - Yiming Sun, Fan Yu, Shaoxiang Chen, Yu Zhang, Junwei Huang, Yang Li, Chenhui Li, Changbo Wang:
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model. - Jin Shin, Hyun Kim:
L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer. - Emre Acartürk, Burak Varici, Karthikeyan Shanmugam, Ali Tajer:
Sample Complexity of Interventional Causal Representation Learning. - Shuaihang Yuan, Hao Huang, Yu Hao, Congcong Wen, Anthony Tzes, Yi Fang:
GAMap: Zero-Shot Object Goal Navigation with Multi-Scale Geometric-Affordance Guidance. - Yiyuan Yang, Guodong Long, Tao Shen, Jing Jiang, Michael Blumenstein:
Dual-Personalizing Adapter for Federated Foundation Models. - Zigeng Chen, Gongfan Fang, Xinyin Ma, Xinchao Wang:
SlimSAM: 0.1% Data Makes Segment Anything Slim. - Samuel Deng, Jingwen Liu, Daniel J. Hsu:
Group-wise oracle-efficient algorithms for online multi-group learning. - Lai Wei, Zhiquan Tan, Chenghai Li, Jindong Wang, Weiran Huang:
Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models. - Qihan Huang, Jie Song, Mengqi Xue, Haofei Zhang, Bingde Hu, Huiqiong Wang, Hao Jiang, Xingen Wang, Mingli Song:
LG-CAV: Train Any Concept Activation Vector with Language Guidance. - Hao Zhang, Lei Cao, Jiayi Ma:
Text-DiFuse: An Interactive Multi-Modal Image Fusion Framework based on Text-modulated Diffusion Model. - Zhiyuan Min, Yawei Luo, Jianwen Sun, Yi Yang:
Epipolar-Free 3D Gaussian Splatting for Generalizable Novel View Synthesis. - Fawaz Sammani, Nikos Deligiannis:
Interpreting and Analysing CLIP's Zero-Shot Image Classification via Mutual Knowledge. - Yoonsoo Nam, Nayara Fonseca, Seok Hyeong Lee, Chris Mingard, Ard A. Louis:
An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem. - Sudeep Salgia, Yuejie Chi:
The Sample-Communication Complexity Trade-off in Federated Q-Learning. - Rui Yang, Jie Wang, Guoping Wu, Bin Li:
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions. - Zhenyu Lou, Qiongjie Cui, Tuo Wang, Zhenbo Song, Luoming Zhang, Cheng Cheng, Haofan Wang, Xu Tang, Huaxia Li, Hong Zhou:
Harmonizing Stochasticity and Determinism: Scene-responsive Diverse Human Motion Prediction. - Bin-Bin Gao:
MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning. - Arna Ghosh, Kumar Krishna Agrawal, Shagun Sodhani, Adam Oberman, Blake A. Richards:
Harnessing small projectors and multiple views for efficient vision pretraining. - Lianyu Pang, Jian Yin, Baoquan Zhao, Feize Wu, Fu Lee Wang, Qing Li, Xudong Mao:
AttnDreamBooth: Towards Text-Aligned Personalized Text-to-Image Generation. - Yiheng Zhu, Jialu Wu, Qiuyi Li, Jiahuan Yan, Mingze Yin, Wei Wu, Mingyang Li, Jieping Ye, Zheng Wang, Jian Wu:
Bridge-IF: Learning Inverse Protein Folding with Markov Bridges. - Eliad Tsfadia:
On Differentially Private Subspace Estimation in a Distribution-Free Setting. - Qiuyi (Richard) Zhang:
Optimal Scalarizations for Sublinear Hypervolume Regret. - Yongsheng Yu, Ziyun Zeng, Hang Hua, Jianlong Fu, Jiebo Luo:
PromptFix: You Prompt and We Fix the Photo. - Zhengrui Xu, Guan'an Wang, Xiaowen Huang, Jitao Sang:
DenoiseRep: Denoising Model for Representation Learning. - Zhilin Zhao, Longbing Cao, Xuhui Fan, Wei-Shi Zheng:
Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data. - Jiaming Liu, Mengzhen Liu, Zhenyu Wang, Pengju An, Xiaoqi Li, Kaichen Zhou, Senqiao Yang, Renrui Zhang, Yandong Guo, Shanghang Zhang:
RoboMamba: Efficient Vision-Language-Action Model for Robotic Reasoning and Manipulation. - Zijian Chen, Wei Sun, Yuan Tian, Jun Jia, Zicheng Zhang, Jiarui Wang, Ru Huang, Xiongkuo Min, Guangtao Zhai, Wen-Jun Zhang:
GAIA: Rethinking Action Quality Assessment for AI-Generated Videos. - MaryBeth Defrance, Maarten Buyl, Tijl De Bie:
ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods. - Xueyan Zou, Linjie Li, Jianfeng Wang, Jianwei Yang, Mingyu Ding, Junyi Wei, Zhengyuan Yang, Feng Li, Hao Zhang, Shilong Liu, Arul Aravinthan, Yong Jae Lee, Lijuan Wang:
Interfacing Foundation Models' Embeddings. - Andy Zhou, Bo Li, Haohan Wang:
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks. - Zhiwen Fan, Jian Zhang, Wenyan Cong, Peihao Wang, Renjie Li, Kairun Wen, Shijie Zhou, Achuta Kadambi, Zhangyang Wang, Danfei Xu, Boris Ivanovic, Marco Pavone:
Large Spatial Model: End-to-end Unposed Images to Semantic 3D. - Chen-Long Duan, Yong Li, Xiu-Shen Wei, Lin Zhao:
Long-tailed Object Detection Pretraining: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction. - Janek Haberer, Ali Hojjat, Olaf Landsiedel:
HydraViT: Stacking Heads for a Scalable ViT. - Byung-Kwan Lee, Chae Won Kim, Beomchan Park, Yong Man Ro:
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models. - Xueyan Niu, Cristina Savin, Eero P. Simoncelli:
Learning predictable and robust neural representations by straightening image sequences. - Kenneth C. Enevoldsen, Márton Kardos, Niklas Muennighoff, Kristoffer L. Nielbo:
The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding. - David Huk, Yuanhe Zhang, Ritabrata Dutta, Mark Steel:
Quasi-Bayes meets Vines. - Houlun Chen, Xin Wang, Hong Chen, Zeyang Zhang, Wei Feng, Bin Huang, Jia Jia, Wenwu Zhu:
VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding. - Matteo Russo, Andrea Celli, Riccardo Colini-Baldeschi, Federico Fusco, Daniel Haimovich, Dima Karamshuk, Stefano Leonardi, Niek Tax:
Online Learning with Sublinear Best-Action Queries. - Chao Wang, Xin He, Yuwen Wang, Junhui Wang:
On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity. - Thomas Nagler, Lennart Schneider, Bernd Bischl, Matthias Feurer:
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization. - Bowen Jing, Hannes Stärk, Tommi S. Jaakkola, Bonnie Berger:
Generative Modeling of Molecular Dynamics Trajectories. - Emanuele Natale, Davide Ferré, Giordano Giambartolomei, Frédéric Giroire, Frederik Mallmann-Trenn:
On the Sparsity of the Strong Lottery Ticket Hypothesis. - Zihan Lu, Chenxu Wang, Chunyan Xu, Xiangwei Zheng, Zhen Cui:
Progressive Exploration-Conformal Learning for Sparsely Annotated Object Detection in Aerial Images. - Tobit Klug, Kun Wang, Stefan Ruschke, Reinhard Heckel:
MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI. - Charles Arnal, David Cohen-Steiner, Vincent Divol:
Wasserstein convergence of Cech persistence diagrams for samplings of submanifolds. - Curt Tigges, Michael Hanna, Qinan Yu, Stella Biderman:
LLM Circuit Analyses Are Consistent Across Training and Scale. - David Bell, Alison Duffy, Adrienne Fairhall:
Discovering plasticity rules that organize and maintain neural circuits. - El Mehdi Saad, Alexandra Carpentier, Tomás Kocák, Nicolas Verzelen:
On Weak Regret Analysis for Dueling Bandits. - Yufei Jin, Heng Lian, Yi He, Xingquan Zhu:
HGDL: Heterogeneous Graph Label Distribution Learning. - Zhenyu Zhou, Defang Chen, Can Wang, Chun Chen, Siwei Lyu:
Simple and Fast Distillation of Diffusion Models. - Fan Zhang, Tianyu Liu, Zihao Chen, Xiaojiang Peng, Chong Chen, Xian-Sheng Hua, Xiao Luo, Hongyu Zhao:
Semi-supervised Knowledge Transfer Across Multi-omic Single-cell Data. - Zinan Lv, Dong Han, Wenzhe Wang, Danny Z. Chen:
A Siamese Transformer with Hierarchical Refinement for Lane Detection. - Thao Nguyen, Haotian Liu, Yuheng Li, Mu Cai, Utkarsh Ojha, Yong Jae Lee:
Yo'LLaVA: Your Personalized Language and Vision Assistant. - Ruijiang Gao, Mingzhang Yin, Maytal Saar-Tsechansky:
SEL-BALD: Deep Bayesian Active Learning with Selective Labels. - Shivam Gupta, Aditya Parulekar, Eric Price, Zhiyang Xun:
Improved Sample Complexity Bounds for Diffusion Model Training. - Feng-Yi Liao, Lijun Ding, Yang Zheng:
Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence. - Youpeng Wen, Junfan Lin, Yi Zhu, Jianhua Han, Hang Xu, Shen Zhao, Xiaodan Liang:
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation. - Saurav Muralidharan, Sharath Turuvekere Sreenivas, Raviraj Joshi, Marcin Chochowski, Mostofa Patwary, Mohammad Shoeybi, Bryan Catanzaro, Jan Kautz, Pavlo Molchanov:
Compact Language Models via Pruning and Knowledge Distillation. - Florian Russold, Michael Kerber:
Graphcode: Learning from multiparameter persistent homology using graph neural networks. - Joshua McClellan, Naveed Haghani, John Winder, Furong Huang, Pratap Tokekar:
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance. - Kiwoong Yoo, Owen Oertell, Junhyun Lee, Sanghoon Lee, Jaewoo Kang:
TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Models. - Liane Vogel, Jan-Micha Bodensohn, Carsten Binnig:
WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata. - Yash Sarrof, Yana Veitsman, Michael Hahn:
The Expressive Capacity of State Space Models: A Formal Language Perspective. - Athanasios Tragakis, Marco Aversa, Chaitanya Kaul, Roderick Murray-Smith, Daniele Faccio:
Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models. - Abhishek Sinha, Rahul Vaze:
Optimal Algorithms for Online Convex Optimization with Adversarial Constraints. - Ziyi Zhou, Xinwei Guo, Jiashi Gao, Xiangyu Zhao, Shiyao Zhang, Xin Yao, Xuetao Wei:
Unveiling the Bias Impact on Symmetric Moral Consistency of Large Language Models. - Kyriakos Lotidis, Angeliki Giannou, Panayotis Mertikopoulos, Nicholas Bambos:
Accelerated Regularized Learning in Finite N-Person Games. - Dmitrii Avdiukhin, Vaggos Chatziafratis, Orr Fischer, Grigory Yaroslavtsev:
Embedding Dimension of Contrastive Learning and k-Nearest Neighbors. - Sahil Bhatia, Jie Qiu, Niranjan Hasabnis, Sanjit Seshia, Alvin Cheung:
Verified Code Transpilation with LLMs. - Vijay Lingam, Atula Neerkaje, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Eunsol Choi, Alex Dimakis, Aleksandar Bojchevski, Sujay Sanghavi:
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors. - Chiyu Ma, Jon Donnelly, Wenjun Liu, Soroush Vosoughi, Cynthia Rudin, Chaofan Chen:
Interpretable Image Classification with Adaptive Prototype-based Vision Transformers. - Yiwei Ma, Jiayi Ji, Ke Ye, Weihuang Lin, Zhibin Wang, Yonghan Zheng, Qiang Zhou, Xiaoshuai Sun, Rongrong Ji:
I2EBench: A Comprehensive Benchmark for Instruction-based Image Editing. - Huiping Zhuang, Yuchen Liu, Run He, Kai Tong, Ziqian Zeng, Cen Chen, Yi Wang, Lap-Pui Chau:
F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning. - Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Johan Decruyenaere, Christiaan Polet, Thomas Demeester, Stijn Vansteelandt:
Debiasing Synthetic Data Generated by Deep Generative Models. - Joel Oskarsson, Tomas Landelius, Marc Peter Deisenroth, Fredrik Lindsten:
Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks. - Xinhao Zheng, Yang Li, Cunxin Fan, Huaijin Wu, Xinhao Song, Junchi Yan:
Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation. - Anqi Mao, Mehryar Mohri, Yutao Zhong:
A Universal Growth Rate for Learning with Smooth Surrogate Losses. - Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin T. Vechev:
Exploiting LLM Quantization. - Kanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh:
Learning Social Welfare Functions. - Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Weijian Deng, Jianfeng Zhang, Bo An:
MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts. - Yidi Shao, Chen Change Loy, Bo Dai:
Learning 3D Garment Animation from Trajectories of A Piece of Cloth. - Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn:
DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction. - Andrea Bonfanti, Giuseppe Bruno, Cristina Cipriani:
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks. - Mingyuan Fan, Xiaodan Li, Cen Chen, Wenmeng Zhou, Yaliang Li:
Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness. - Michal Balcerak, Tamaz Amiranashvili, Andreas Wagner, Jonas Weidner, Petr Karnakov, Johannes C. Paetzold, Ivan Ezhov, Petros Koumoutsakos, Benedikt Wiestler, Bjoern H. Menze:
Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization. - George Christodoulou, Alkmini Sgouritsa, Ioannis Vlachos:
Mechanism design augmented with output advice. - Sebastian Damrich, Philipp Berens, Dmitry Kobak:
Persistent Homology for High-dimensional Data Based on Spectral Methods. - Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi:
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries. - Leyang Shen, Gongwei Chen, Rui Shao, Weili Guan, Liqiang Nie:
MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models. - Anwesa Choudhuri, Girish Chowdhary, Alexander G. Schwing:
OW-VISCapTor: Abstractors for Open-World Video Instance Segmentation and Captioning. - Weilin Lin, Li Liu, Shaokui Wei, Jianze Li, Hui Xiong:
Unveiling and Mitigating Backdoor Vulnerabilities based on Unlearning Weight Changes and Backdoor Activeness. - Ziyad Benomar, Dorian Baudry, Vianney Perchet:
Lookback Prophet Inequalities. - Alexander Havrilla, Wenjing Liao:
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data. - Ivana Kajic, Olivia Wiles, Isabela Albuquerque, Matthias Bauer, Su Wang, Jordi Pont-Tuset, Aida Nematzadeh:
Evaluating Numerical Reasoning in Text-to-Image Models. - Paulius Rauba, Nabeel Seedat, Krzysztof Kacprzyk, Mihaela van der Schaar:
Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments. - Kushal Kardam Vyas, Ahmed Imtiaz Humayun, Aniket Dashpute, Richard G. Baraniuk, Ashok Veeraraghavan, Guha Balakrishnan:
Learning Transferable Features for Implicit Neural Representations. - Roy Miles, Pradyumna Reddy, Ismail Elezi, Jiankang Deng:
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections. - Trenton Chang, Lindsay A. Warrenburg, Sae-Hwan Park, Ravi B. Parikh, Maggie Makar, Jenna Wiens:
Who's Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation. - Yuhan Li, Peisong Wang, Xiao Zhu, Aochuan Chen, Haiyun Jiang, Deng Cai, Wai Kin (Victor) Chan, Jia Li:
GLBench: A Comprehensive Benchmark for Graph with Large Language Models. - Honglin Liu, Peng Hu, Changqing Zhang, Yunfan Li, Xi Peng:
Interactive Deep Clustering via Value Mining. - Raphaël Baena, Syrine Kalleli, Mathieu Aubry:
General Detection-based Text Line Recognition. - Tianyu Chen, Kevin Bello, Francesco Locatello, Bryon Aragam, Pradeep Ravikumar:
Identifying General Mechanism Shifts in Linear Causal Representations. - Ahmad-Reza Ehyaei, Golnoosh Farnadi, Samira Samadi:
Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness. - Yinghao Wu, Chaoran Wang, Lu Yin, Shihui Guo, Yipeng Qin:
Accurate and Steady Inertial Pose Estimation through Sequence Structure Learning and Modulation. - Shaoqi Wang, Chunjie Yang, Siwei Lou:
Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient. - David Castillo-Bolado, Joseph Davidson, Finlay Gray, Marek Rosa:
Beyond Prompts: Dynamic Conversational Benchmarking of Large Language Models. - Xiaoyi Dong, Pan Zhang, Yuhang Zang, Yuhang Cao, Bin Wang, Linke Ouyang, Songyang Zhang, Haodong Duan, Wenwei Zhang, Yining Li, Hang Yan, Yang Gao, Zhe Chen, Xinyue Zhang, Wei Li, Jingwen Li, Wenhai Wang, Kai Chen, Conghui He, Xingcheng Zhang, Jifeng Dai, Yu Qiao, Dahua Lin, Jiaqi Wang:
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD. - Xiaoming Zhao, Pratul P. Srinivasan, Dor Verbin, Keunhong Park, Ricardo Martin-Brualla, Philipp Henzler:
IllumiNeRF: 3D Relighting Without Inverse Rendering. - Hyeonah Kim, Minsu Kim, Sanghyeok Choi, Jinkyoo Park:
Genetic-guided GFlowNets for Sample Efficient Molecular Optimization. - Yitian Zhang, Huseyin Coskun, Xu Ma, Huan Wang, Ke Ma, Xi Stephen Chen, Derek Hao Hu, Yun Fu:
Slicing Vision Transformer for Flexible Inference. - Muzhi Zhu, Yang Liu, Zekai Luo, Chenchen Jing, Hao Chen, Guangkai Xu, Xinlong Wang, Chunhua Shen:
Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation. - Anthony Bardou, Patrick Thiran, Giovanni Ranieri:
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization. - Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree P. Vadgama, Thijs P. Kuipers, Erik J. Bekkers:
Learning symmetries via weight-sharing with doubly stochastic tensors. - Qinpeng Cui, Yixuan Liu, Xinyi Zhang, Qiqi Bao, Qingmin Liao, liwang Amd, Lu Tian, Zicheng Liu, Zhongdao Wang, Emad Barsoum:
Taming Diffusion Prior for Image Super-Resolution with Domain Shift SDEs. - Steve Hanneke, Shay Moran, Qian Zhang:
Improved Sample Complexity for Multiclass PAC Learning. - Dylan J. Foster, Yanjun Han, Jian Qian, Alexander Rakhlin:
Online Estimation via Offline Estimation: An Information-Theoretic Framework. - Paul Pu Liang, Akshay Goindani, Talha Chafekar, Leena Mathur, Haofei Yu, Ruslan Salakhutdinov, Louis-Philippe Morency:
HEMM: Holistic Evaluation of Multimodal Foundation Models. - Lei Zhu, Xinjiang Wang, Wayne Zhang, Rynson W. H. Lau:
Revisiting the Integration of Convolution and Attention for Vision Backbone. - Yiming Wang, Pei Zhang, Baosong Yang, Derek F. Wong, Zhuosheng Zhang, Rui Wang:
Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning. - Amrith Setlur, Saurabh Garg, Xinyang Geng, Naman Garg, Virginia Smith, Aviral Kumar:
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold. - Gabriel Poesia, David Broman, Nick Haber, Noah D. Goodman:
Learning Formal Mathematics From Intrinsic Motivation. - Wonguk Cho, Seokeon Choi, Debasmit Das, Matthias Reisser, Taesup Kim, Sungrack Yun, Fatih Porikli:
Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models. - Elias Stengel-Eskin, Peter Hase, Mohit Bansal:
LACIE: Listener-Aware Finetuning for Calibration in Large Language Models. - Jianfeng Dong, Xiaoman Peng, Daizong Liu, Xiaoye Qu, Xun Yang, Cuizhu Bao, Meng Wang:
Temporal Sentence Grounding with Relevance Feedback in Videos. - Yujie Mo, Zhihe Lu, Runpeng Yu, Xiaofeng Zhu, Xinchao Wang:
Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective. - Tang Li, Mengmeng Ma, Xi Peng:
Beyond Accuracy: Ensuring Correct Predictions With Correct Rationales. - Hao Deng, Kunlei Jing, Shengmei Chen, Cheng Liu, Jiawei Ru, Bo Jiang, Lin Wang:
LinNet: Linear Network for Efficient Point Cloud Representation Learning. - Ziang Chen, Rong Ge:
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input. - Filip Szatkowski, Bartosz Wójcik, Mikolaj Piórczynski, Simone Scardapane:
Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion. - Hong Jia, Young Kwon, Alessio Orsino, Ting Dang, Domenico Talia, Cecilia Mascolo:
TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices. - Baekrok Shin, Junsoo Oh, Hanseul Cho, Chulhee Yun:
DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity. - Shiyu Xia, Yuankun Zu, Xu Yang, Xin Geng:
Initializing Variable-sized Vision Transformers from Learngene with Learnable Transformation. - Yijun Dong, Viet Hoang Phan, Xiang Pan, Qi Lei:
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning. - Filip Granqvist, Congzheng Song, Áine Cahill, Rogier C. van Dalen, Martin Pelikan, Yi Sheng Chan, Xiaojun Feng, Natarajan Krishnaswami, Vojta Jina, Mona Chitnis:
pfl-research: simulation framework for accelerating research in Private Federated Learning. - Sharath Girish, Tianye Li, Amrita Mazumdar, Abhinav Shrivastava, David Luebke, Shalini De Mello:
QUEEN: QUantized Efficient ENcoding of Dynamic Gaussians for Streaming Free-viewpoint Videos. - Guanqi Zhan, Chuanxia Zheng, Weidi Xie, Andrew Zisserman:
A General Protocol to Probe Large Vision Models for 3D Physical Understanding. - Dhananjay Tomar, Alexander Binder, Andreas Kleppe:
Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology. - Tyler Bonnen, Stephanie Fu, Yutong Bai, Thomas P. O'Connell, Yoni Friedman, Nancy Kanwisher, Josh Tenenbaum, Alexei A. Efros:
Evaluating Multiview Object Consistency in Humans and Image Models. - Jun Xia, Zhihao Yue, Yingbo Zhou, Zhiwei Ling, Yiyu Shi, Xian Wei, Mingsong Chen:
WaveAttack: Asymmetric Frequency Obfuscation-based Backdoor Attacks Against Deep Neural Networks. - Haoran Ye, Jiarui Wang, Zhiguang Cao, Federico Berto, Chuanbo Hua, Haeyeon Kim, Jinkyoo Park, Guojie Song:
ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution. - Cuong Le, John Viktor Johansson, Manon Kok, Bastian Wandt:
Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos. - Yeonsung Jung, Jaeyun Song, June Yong Yang, Jin-Hwa Kim, Sungyub Kim, Eunho Yang:
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective. - Yuchen Ma, Valentyn Melnychuk, Jonas Schweisthal, Stefan Feuerriegel:
DiffPO: A causal diffusion model for learning distributions of potential outcomes. - Seungjoo Lee, Thanh-Long V. Le, Jaemin Shin, Sung-Ju Lee:
(FL)2: Overcoming Few Labels in Federated Semi-Supervised Learning. - Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine:
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction. - Victor Zhong, Dipendra Misra, Xingdi Yuan, Marc-Alexandre Côté:
Policy Improvement using Language Feedback Models. - Enyi Jiang, Gagandeep Singh:
RAMP: Boosting Adversarial Robustness Against Multiple lp Perturbations for Universal Robustness. - Ruize Zhang, Sheng Tang, Juan Cao:
Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation. - Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov:
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. - Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash, Matthias Grossglauser:
Causal Effect Identification in a Sub-Population with Latent Variables. - Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang, Sarah Parisot:
Generating compositional scenes via Text-to-image RGBA Instance Generation. - Y. Jennifer Sun, Zhou Lu:
Tight Rates for Bandit Control Beyond Quadratics. - Taesik Gong, Fahim Kawsar, Chulhong Min:
DEX: Data Channel Extension for Efficient CNN Inference on Tiny AI Accelerators. - Alvin Heng, Alexandre H. Thiery, Harold Soh:
Out-of-Distribution Detection with a Single Unconditional Diffusion Model. - Jeongjin Park, Nicole Yang, Nisha Chandramoorthy:
When are dynamical systems learned from time series data statistically accurate? - Michael S. Yao, Yimeng Zeng, Hamsa Bastani, Jacob R. Gardner, James C. Gee, Osbert Bastani:
Generative Adversarial Model-Based Optimization via Source Critic Regularization. - Siyi Gu, Minkai Xu, Alexander S. Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon:
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization. - Changho Shin, Jitian Zhao, Sonia Cromp, Harit Vishwakarma, Frederic Sala:
OTTER: Effortless Label Distribution Adaptation of Zero-shot Models. - Matthew B. A. McDermott, Haoran Zhang, Lasse Hyldig Hansen, Giovanni Angelotti, Jack Gallifant:
A Closer Look at AUROC and AUPRC under Class Imbalance. - HyunJun Jung, Weihang Li, Shun-Cheng Wu, William Bittner, Nikolas Brasch, Jifei Song, Eduardo Pérez-Pellitero, Zhensong Zhang, Arthur Moreau, Nassir Navab, Benjamin Busam:
SCRREAM : SCan, Register, REnder And Map: A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark. - Nick Huang, Aaron Gokaslan, Volodymyr Kuleshov, James Tompkin:
The GAN is dead; long live the GAN! A Modern GAN Baseline. - Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster:
Amortized Active Causal Induction with Deep Reinforcement Learning. - Chao Li, Zijie Guo, Qiuting He, Kun He:
Long-range Meta-path Search on Large-scale Heterogeneous Graphs. - Jie Ji, Gen Li, Jingjing Fu, Fatemeh Afghah, Linke Guo, Xiaoyong Yuan, Xiaolong Ma:
A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training. - Zhaoqiang Liu, Wen Li, Junren Chen:
Generalized Eigenvalue Problems with Generative Priors. - Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Animashree Anandkumar, Furong Huang:
Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. - Odelia Melamed, Gilad Yehudai, Adi Shamir:
MALT Powers Up Adversarial Attacks. - Xuweiyi Chen, Ziqiao Ma, Xuejun Zhang, Sihan Xu, Shengyi Qian, Jianing Yang, David Fouhey, Joyce Chai:
Multi-Object Hallucination in Vision Language Models. - Yash Savani, Marc Finzi, J. Zico Kolter:
Diffusing Differentiable Representations. - Bingcong Li, Liang Zhang, Niao He:
Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problems. - Lin Duan, Jingwei Sun, Jinyuan Jia, Yiran Chen, Maria Gorlatova:
Reimagining Mutual Information for Enhanced Defense against Data Leakage in Collaborative Inference. - Adriana Hugessen, Harley Wiltzer, Glen Berseth:
Simplifying Constraint Inference with Inverse Reinforcement Learning. - Weihua Du, Qiushi Lyu, Jiaming Shan, Zhenting Qi, Hongxin Zhang, Sunli Chen, Andi Peng, Tianmin Shu, Kwonjoon Lee, Behzad Dariush, Chuang Gan:
Constrained Human-AI Cooperation: An Inclusive Embodied Social Intelligence Challenge. - Haoming Cai, Jingxi Chen, Brandon Y. Feng, Weiyun Jiang, Mingyang Xie, Kevin Zhang, Cornelia Fermüller, Yiannis Aloimonos, Ashok Veeraraghavan, Christopher A. Metzler:
Temporally Consistent Atmospheric Turbulence Mitigation with Neural Representations. - Yuki Takezawa, Han Bao, Ryoma Sato, Kenta Niwa, Makoto Yamada:
Parameter-free Clipped Gradient Descent Meets Polyak. - Zitong Lan, Chenhao Zheng, Zhiwei Zheng, Mingmin Zhao:
Acoustic Volume Rendering for Neural Impulse Response Fields. - Kuan-Yu Chen, Ping-Han Chiang, Hsin-Rung Chou, Chih-Sheng Chen, Tien-Hao Chang:
DOFEN: Deep Oblivious Forest ENsemble. - Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, Miles Cranmer, Swarat Chaudhuri:
Symbolic Regression with a Learned Concept Library. - Oleksii Kachaiev, Stefano Recanatesi:
Learning to Embed Distributions via Maximum Kernel Entropy. - Yang Li, Wenhao Zhang, Jianhong Wang, Shao Zhang, Yali Du, Ying Wen, Wei Pan:
Aligning Individual and Collective Objectives in Multi-Agent Cooperation. - Wen-Ding Li, Kevin Ellis:
Is Programming by Example Solved by LLMs? - Bo Miao, Mingtao Feng, Zijie Wu, Mohammed Bennamoun, Yongsheng Gao, Ajmal Mian:
Referring Human Pose and Mask Estimation In the Wild. - Deep Shankar Pandey, Spandan Pyakurel, Qi Yu:
Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models. - Zhi Wang, Li Zhang, Wenhao Wu, Yuanheng Zhu, Dongbin Zhao, Chunlin Chen:
Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement. - Hadi Vafaii, Dekel Galor, Jacob L. Yates:
Poisson Variational Autoencoder. - Ruyi Zha, Tao Jun Lin, Yuanhao Cai, Jiwen Cao, Yanhao Zhang, Hongdong Li:
R2-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction. - Qiheng Sun, Haocheng Xia, Jinfei Liu:
Data-faithful Feature Attribution: Mitigating Unobservable Confounders via Instrumental Variables. - Hanzhe Li, Jiaran Zhou, Yuezun Li, Baoyuan Wu, Bin Li, Junyu Dong:
FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge. - Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina J. Agocs, Miguel Beneitez, Marsha Berger, Blakesley Burkhart, Stuart B. Dalziel, Drummond B. Fielding, Daniel Fortunato, Jared A. Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich R. Kerswell, Suryanarayana Maddu, Jonah Miller, Payel Mukhopadhyay, Stefan S. Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, François Rozet, Liam Holden Parker, Miles D. Cranmer, Shirley Ho:
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning. - Ilias Diakonikolas, Lisheng Ren, Nikos Zarifis:
Reliable Learning of Halfspaces under Gaussian Marginals. - Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin P. Murphy, Tim Salimans, Ben Poole, Ruiqi Gao:
EM Distillation for One-step Diffusion Models. - Hao Chen, Yufei Zhu, Yongjian Deng:
A Motion-aware Spatio-temporal Graph for Video Salient Object Ranking. - Jincheng Cao, Ruichen Jiang, Erfan Yazdandoost Hamedani, Aryan Mokhtari:
An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization. - Josh Gardner, Juan C. Perdomo, Ludwig Schmidt:
Large Scale Transfer Learning for Tabular Data via Language Modeling. - Mingrui Wu, Xinyue Cai, Jiayi Ji, Jiale Li, Oucheng Huang, Gen Luo, Hao Fei, Guannan Jiang, Xiaoshuai Sun, Rongrong Ji:
ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models. - Yajing Zheng, Jiyuan Zhang, Zhaofei Yu, Tiejun Huang:
Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation. - Heng Yu, Chaoyang Wang, Peiye Zhuang, Willi Menapace, Aliaksandr Siarohin, Junli Cao, László A. Jeni, Sergey Tulyakov, Hsin-Ying Lee:
4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models. - Leon Klein, Frank Noé:
Transferable Boltzmann Generators. - Roy Abel, Shimon Ullman:
Biologically Inspired Learning Model for Instructed Vision. - Tengxiao Liu, Qipeng Guo, Xiangkun Hu, Cheng Jiayang, Yue Zhang, Xipeng Qiu, Zheng Zhang:
Can Language Models Learn to Skip Steps? - Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian:
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random. - Shijin Duan, Ruyi Ding, Jiaxing He, Aidong Adam Ding, Yunsi Fei, Xiaolin Xu:
GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction. - Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low:
Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization. - Lei Huang, Lei Xiong, Na Sun, Zunpeng Liu, Ka-Chun Wong, Manolis Kellis:
A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis. - Yifei Zhang, Huan-ang Gao, Zhou Jiang, Hao Zhao:
Dual-frame Fluid Motion Estimation with Test-time Optimization and Zero-divergence Loss. - Viet Hoang Phan, Tung Lam Tran, Quyen Tran, Trung Le:
Enhancing Domain Adaptation through Prompt Gradient Alignment. - Huanxuan Liao, Shizhu He, Yao Xu, Yuanzhe Zhang, Yanchao Hao, Shengping Liu, Kang Liu, Jun Zhao:
From Instance Training to Instruction Learning: Task Adapters Generation from Instructions. - Chenxin Li, Yuzhi Huang, Wuyang Li, Hengyu Liu, Xinyu Liu, Qing Xu, Zhen Chen, Yue Huang, Yixuan Yuan:
Flaws can be Applause: Unleashing Potential of Segmenting Ambiguous Objects in SAM. - Maxim Nikolaev, Mikhail Kuznetsov, Dmitry P. Vetrov, Aibek Alanov:
HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach. - Dingrong Wang, Hitesh Sapkota, Qi Yu:
Adaptive Important Region Selection with Reinforced Hierarchical Search for Dense Object Detection. - Jialong Zuo, Jiahao Hong, Feng Zhang, Changqian Yu, Hanyu Zhou, Changxin Gao, Nong Sang, Jingdong Wang:
PLIP: Language-Image Pre-training for Person Representation Learning. - Jiaxu Wang, Jingkai Sun, Ziyi Zhang, Junhao He, Qiang Zhang, Mingyuan Sun, Renjing Xu:
DEL: Discrete Element Learner for Learning 3D Particle Dynamics with Neural Rendering. - Dongting Hu, Huan Fu, Jiaxian Guo, Liuhua Peng, Tingjin Chu, Feng Liu, Tongliang Liu, Mingming Gong:
In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment. - Lingjiao Chen, Jared Quincy Davis, Boris Hanin, Peter Bailis, Ion Stoica, Matei A. Zaharia, James Y. Zou:
Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems. - Zhaomin Wu, Junyi Hou, Yiqun Diao, Bingsheng He:
Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data. - Song Ouyang, Huiyu Cai, Yong Luo, Kehua Su, Lefei Zhang, Bo Du:
MMSite: A Multi-modal Framework for the Identification of Active Sites in Proteins. - Ricardo Dominguez-Olmedo, Moritz Hardt, Celestine Mendler-Dünner:
Questioning the Survey Responses of Large Language Models. - Yilong Chen, Linhao Zhang, Junyuan Shang, Zhenyu Zhang, Tingwen Liu, Shuohuan Wang, Yu Sun:
DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion. - Zhiwei Bai, Jiajie Zhao, Yaoyu Zhang:
Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion. - Jun-Hyuk Kim, Seungeon Kim, Won-Hee Lee, Dokwan Oh:
Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec. - Xudong Gong, Dawei Feng, Kele Xu, Bo Ding, Huaimin Wang:
Goal-Conditioned On-Policy Reinforcement Learning. - Wolfgang Boettcher, Lukas Hoyer, Ozan Unal, Jan Eric Lenssen, Bernt Schiele:
Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets. - Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood:
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions. - Hongru Yang, Bhavya Kailkhura, Zhangyang Wang, Yingbin Liang:
Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis. - Fangyikang Wang, Hubery Yin, Yuejiang Dong, Huminhao Zhu, Zhang Chao, Hanbin Zhao, Hui Qian, Chen Li:
BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models. - Justin Singh Kang, Yigit Efe Erginbas, Landon Butler, Ramtin Pedarsani, Kannan Ramchandran:
Learning to Understand: Identifying Interactions via the Möbius Transform. - Guangji Bai, Yijiang Li, Chen Ling, Kibaek Kim, Liang Zhao:
SparseLLM: Towards Global Pruning of Pre-trained Language Models. - Calvin Luo, Mandy He, Zilai Zeng, Chen Sun:
Text-Aware Diffusion for Policy Learning. - Mahdi Haghifam, Thomas Steinke, Jonathan R. Ullman:
Private Geometric Median. - Jiarui Wu, Yujin Wang, Lingen Li, Zhang Fan, Tianfan Xue:
Goal Conditioned Reinforcement Learning for Photo Finishing Tuning. - Kyungeun Lee, Wonjong Rhee:
A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets. - Amrith Setlur, Vitaly Feldman, Kunal Talwar:
Private and Personalized Frequency Estimation in a Federated Setting. - Ziqiang Liu, Feiteng Fang, Xi Feng, Xeron Du, Chenhao Zhang, Noah Wang, Yuelin Bai, Qixuan Zhao, Liyang Fan, Chengguang Gan, Hongquan Lin, Jiaming Li, Yuansheng Ni, Haihong Wu, Yaswanth Narsupalli, Zhigang Zheng, Chengming Li, Xiping Hu, Ruifeng Xu, Xiaojun Chen, Min Yang, Jiaheng Liu, Ruibo Liu, Wenhao Huang, Ge Zhang, Shiwen Ni:
II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models. - Mo Zhou, Rong Ge:
How does Gradient Descent Learn Features - A Local Analysis for Regularized Two-Layer Neural Networks. - Penghui Qi, Xinyi Wan, Nyamdavaa Amar, Min Lin:
Pipeline Parallelism with Controllable Memory. - Yifan Jiang, Jiarui Zhang, Kexuan Sun, Zhivar Sourati, Kian Ahrabian, Kaixin Ma, Filip Ilievski, Jay Pujara:
MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learning. - Hang Guo, Tao Dai, Zhihao Ouyang, Taolin Zhang, Yaohua Zha, Bin Chen, Shu-Tao Xia:
ReFIR: Grounding Large Restoration Models with Retrieval Augmentation. - Zeyang Liu, Xinrui Yang, Shiguang Sun, Long Qian, Lipeng Wan, Xingyu Chen, Xuguang Lan:
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model. - Shiqi Sun, Yantao Lu, Ning Liu, Bo Jiang, Jinchao Chen, Ying Zhang:
AlterMOMA: Fusion Redundancy Pruning for Camera-LiDAR Fusion Models with Alternative Modality Masking. - Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi:
Loss Landscape Characterization of Neural Networks without Over-Parametrization. - Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan, Ruqi Zhang:
Gradient-based Discrete Sampling with Automatic Cyclical Scheduling. - Yifan Sun, Jingyan Shen, Yongchan Kwon:
2D-OOB: Attributing Data Contribution Through Joint Valuation Framework. - Benjamin Minixhofer, Edoardo Maria Ponti, Ivan Vulic:
Zero-Shot Tokenizer Transfer. - Hugh Zhang, Jeff Da, Dean Lee, Vaughn Robinson, Catherine Wu, William Song, Tiffany Zhao, Pranav Raja, Charlotte Zhuang, Dylan Slack, Qin Lyu, Sean Hendryx, Russell Kaplan, Michele Lunati, Summer Yue:
A Careful Examination of Large Language Model Performance on Grade School Arithmetic. - Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Theoretical Analysis of Weak-to-Strong Generalization. - Yi-Lin Wei, Jian-Jian Jiang, Chengyi Xing, Xiantuo Tan, Xiao-Ming Wu, Hao Li, Mark R. Cutkosky, Wei-Shi Zheng:
Grasp as You Say: Language-guided Dexterous Grasp Generation. - Michal Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gainski, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey:
RGFN: Synthesizable Molecular Generation Using GFlowNets. - Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E:
Exploring Molecular Pretraining Model at Scale. - Elvis Dohmatob, Yunzhen Feng, Julia Kempe:
Model Collapse Demystified: The Case of Regression. - Timothy Chu, Josh Alman, Gary L. Miller, Shyam Narayanan, Mark Sellke, Zhao Song:
Metric Transforms and Low Rank Representations of Kernels for Fast Attention. - Yoonki Cho, Jaeyoon Kim, Woo Jae Kim, Junsik Jung, Sung-Eui Yoon:
Generalizable Person Re-identification via Balancing Alignment and Uniformity. - Liwei Jiang, Kavel Rao, Seungju Han, Allyson Ettinger, Faeze Brahman, Sachin Kumar, Niloofar Mireshghallah, Ximing Lu, Maarten Sap, Yejin Choi, Nouha Dziri:
WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models. - Zhe Hu, Tuo Liang, Jing Li, Yiren Lu, Yunlai Zhou, Yiran Qiao, Jing Ma, Yu Yin:
Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions. - Yuma Ichikawa:
Controlling Continuous Relaxation for Combinatorial Optimization. - Qing Xu, Min Wu, Xiaoli Li, Kezhi Mao, Zhenghua Chen:
Reinforced Cross-Domain Knowledge Distillation on Time Series Data. - Mingsheng Li, Jiakang Yuan, Sijin Chen, Lin Zhang, Anyu Zhu, Xin Chen, Tao Chen:
3DET-Mamba: Causal Sequence Modelling for End-to-End 3D Object Detection. - Chaitanya Murti, Chiranjib Bhattacharyya:
DisCEdit: Model Editing by Identifying Discriminative Components. - Abhinav Jain, Swarat Chaudhuri, Thomas W. Reps, Christopher M. Jermaine:
Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation. - Parsa Esmati, Amirhossein Dadashzadeh, Vahid Ardakani, Nicolas Larrosa, Nicolò Grilli:
SEA: State-Exchange Attention for High-Fidelity Physics Based Transformers. - Xihuai Wang, Shao Zhang, Wenhao Zhang, Wentao Dong, Jingxiao Chen, Ying Wen, Weinan Zhang:
ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination. - Yabing Wang, Zhuotao Tian, Qingpei Guo, Zheng Qin, Sanping Zhou, Ming Yang, Le Wang:
Referencing Where to Focus: Improving Visual Grounding with Referential Query. - Sayantan Choudhury, Nazarii Tupitsa, Nicolas Loizou, Samuel Horváth, Martin Takác, Eduard Gorbunov:
Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad. - Shuqi Li, Yuebo Sun, Yuxin Lin, Xin Gao, Shuo Shang, Rui Yan:
CausalStock: Deep End-to-end Causal Discovery for News-driven Multi-stock Movement Prediction. - Tianwei Yin, Michaël Gharbi, Taesung Park, Richard Zhang, Eli Shechtman, Frédo Durand, Bill Freeman:
Improved Distribution Matching Distillation for Fast Image Synthesis. - Yu-Zhe Shi, Fanxu Meng, Haofei Hou, Zhangqian Bi, Qiao Xu, Lecheng Ruan, Qining Wang:
Expert-level protocol translation for self-driving labs. - Liang Qin, Xiyuan Liu, Wenting Wei, Chengbin Liang, Huaxi Gu:
Satformer: Accurate and Robust Traffic Data Estimation for Satellite Networks. - Andong Wang, Yuning Qiu, Mingyuan Bai, Zhong Jin, Guoxu Zhou, Qibin Zhao:
Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts. - Jiawei Zhang, Jiaxin Zhuang, Cheng Jin, Gen Li, Yuantao Gu:
Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems. - Milad Khademi Nori, Il-Min Kim:
Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings. - Vincent Roulet, Atish Agarwala, Jean-Bastien Grill, Grzegorz Swirszcz, Mathieu Blondel, Fabian Pedregosa:
Stepping on the Edge: Curvature Aware Learning Rate Tuners. - Hyunseung Kim, Byungkun Lee, Hojoon Lee, Dongyoon Hwang, Donghu Kim, Jaegul Choo:
Do's and Don'ts: Learning Desirable Skills with Instruction Videos. - Zheng Zhang, Wei Song, Qi Liu, Qingyang Mao, Yiyan Wang, Weibo Gao, Zhenya Huang, Shijin Wang, Enhong Chen:
Towards Accurate and Fair Cognitive Diagnosis via Monotonic Data Augmentation. - Orevaoghene Ahia, Sachin Kumar, Hila Gonen, Valentin Hofmann, Tomasz Limisiewicz, Yulia Tsvetkov, Noah A. Smith:
MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization. - Harley Wiltzer, Marc G. Bellemare, David Meger, Patrick Shafto, Yash Jhaveri:
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning. - Jiashi Gao, Ziwei Wang, Xiangyu Zhao, Xin Yao, Xuetao Wei:
Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors. - Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye:
Counterfactual Fairness by Combining Factual and Counterfactual Predictions. - Qingsong Zhao, Yi Wang, Jilan Xu, Yinan He, Zifan Song, Limin Wang, Yu Qiao, Cairong Zhao:
Does Video-Text Pretraining Help Open-Vocabulary Online Action Detection? - Theodore Brown, Alexandru Cioba, Ilija Bogunovic:
Sample-efficient Bayesian Optimisation Using Known Invariances. - Shelly Golan, Roy Ganz, Michael Elad:
Enhancing Consistency-Based Image Generation via Adversarialy-Trained Classification and Energy-Based Discrimination. - Kai Hu, Ye Xiao, Yuan Zhang, Xieping Gao:
Multi-view Masked Contrastive Representation Learning for Endoscopic Video Analysis. - David Osowiechi, Mehrdad Noori, Gustavo Adolfo Vargas Hakim, Moslem Yazdanpanah, Ali Bahri, Milad Cheraghalikhani, Sahar Dastani, Farzad Beizaee, Ismail Ben Ayed, Christian Desrosiers:
WATT: Weight Average Test Time Adaptation of CLIP. - Jiawen Zhang, Xumeng Wen, Zhenwei Zhang, Shun Zheng, Jia Li, Jiang Bian:
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons. - Duo Cheng, Xingyu Zhou, Bo Ji:
Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting. - Jingwei Li, Jing Dong, Can Chang, Baoxiang Wang, Jingzhao Zhang:
Online Control with Adversarial Disturbance for Continuous-time Linear Systems. - Bastian Epping, Alexandre René, Moritz Helias, Michael T. Schaub:
Graph Neural Networks Do Not Always Oversmooth. - Qianyue Hao, Jingyang Fan, Fengli Xu, Jian Yuan, Yong Li:
HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction. - Yujie Lu, Dongfu Jiang, Wenhu Chen, William Yang Wang, Yejin Choi, Bill Yuchen Lin:
WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences. - Feng Xie, Zhen Yao, Lin Xie, Yan Zeng, Zhi Geng:
Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments. - Ruiyu Mao, Sarthak Kumar Maharana, Rishabh K. Iyer, Yunhui Guo:
STONE: A Submodular Optimization Framework for Active 3D Object Detection. - Kai Tan, Pierre C. Bellec:
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression. - Mohamed Ghanem, Frederik Schmitt, Julian Siber, Bernd Finkbeiner:
Learning Better Representations From Less Data For Propositional Satisfiability. - Zhihao Dai, Ligang He, Shuanghua Yang, Matthew Leeke:
SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series. - Tassilo Wald, Constantin Ulrich, Priyank Jaini, Gregor Köhler, David Zimmerer, Stefan Denner, Fabian Isensee, Michael Baumgartner, Klaus H. Maier-Hein:
Decoupling Semantic Similarity from Spatial Alignment for Neural Networks. - Roland S. Zimmermann, David A. Klindt, Wieland Brendel:
Measuring Per-Unit Interpretability at Scale Without Humans. - Fan-Ming Luo, Zuolin Tu, Zefang Huang, Yang Yu:
Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rate. - Yash Mehta, Danil Tyulmankov, Adithya Rajagopalan, Glenn Turner, James Fitzgerald, Jan Funke:
Model Based Inference of Synaptic Plasticity Rules. - Jianqing Song, Jianguo Huang, Wenyu Jiang, Baoming Zhang, Shuangjie Li, Chongjun Wang:
Similarity-Navigated Conformal Prediction for Graph Neural Networks. - Edward Bartrum, Thu Nguyen-Phuoc, Christopher Xie, Zhengqin Li, Numair Khan, Armen Avetisyan, Douglas Lanman, Lei Xiao:
ReplaceAnything3D: Text-Guided Object Replacement in 3D Scenes with Compositional Scene Representations. - Eli Sennesh, Hao Wu, Tommaso Salvatori:
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm. - Hoang Tran, Thieu Vo, Tho Huu, An Nguyen The, Tan Nguyen:
Monomial Matrix Group Equivariant Neural Functional Networks. - Xiyuan Li, Weiwei Liu:
Error Analysis of Spherically Constrained Least Squares Reformulation in Solving the Stackelberg Prediction Game. - Antonios Alexos, Junze Liu, Shashank Galla, Sean Hayes, Kshitij Bhardwaj, Alexander Schwartz, Monika Biener, Pierre Baldi, Satish T. S. Bukkapatnam, Suhas Bhandarkar:
Nuclear Fusion Diamond Polishing Dataset. - Eduardo Laber, Miguel Batista:
On the cohesion and separability of average-link for hierarchical agglomerative clustering. - Namgyu Ho, Sangmin Bae, Taehyeon Kim, Hyunjik Jo, Yireun Kim, Tal Schuster, Adam Fisch, James Thorne, Se-Young Yun:
Block Transformer: Global-to-Local Language Modeling for Fast Inference. - Max Vladymyrov, Johannes von Oswald, Mark Sandler, Rong Ge:
Linear Transformers are Versatile In-Context Learners. - Niki Amini-Naieni, Tengda Han, Andrew Zisserman:
CountGD: Multi-Modal Open-World Counting. - Yunsong Zhou, Michael Simon, Zhenghao Mark Peng, Sicheng Mo, Hongzi Zhu, Minyi Guo, Bolei Zhou:
SimGen: Simulator-conditioned Driving Scene Generation. - Ruizhe Shi, Yifang Chen, Yushi Hu, Alisa Liu, Hanna Hajishirzi, Noah A. Smith, Simon S. Du:
Decoding-Time Language Model Alignment with Multiple Objectives. - Aditya Desai, Kimia Saedi, Apoorv Walia, Jihyeong Lee, Keren Zhou, Anshumali Shrivastava:
SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform. - Xuan Ju, Yiming Gao, Zhaoyang Zhang, Ziyang Yuan, Xintao Wang, Ailing Zeng, Yu Xiong, Qiang Xu, Ying Shan:
MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions. - Yuxin Yang, Qiang Li, Yuan Hong, Binghui Wang:
FedGMark: Certifiably Robust Watermarking for Federated Graph Learning. - Mengyi Chen, Qianxiao Li:
Learning Macroscopic Dynamics from Partial Microscopic Observations. - Simon Geisler, Arthur Kosmala, Daniel Herbst, Stephan Günnemann:
Spatio-Spectral Graph Neural Networks. - Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li:
On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability. - Ruihan Guo, Rui Wang, Ruidong Wu, Zhizhou Ren, Jiahan Li, Shitong Luo, Zuofan Wu, Qiang Liu, Jian Peng, Jianzhu Ma:
Enhancing Protein Mutation Effect Prediction through a Retrieval-Augmented Framework. - Chengkai Hou, Zhengrong Xue, Bingyang Zhou, Jinghan Ke, Lin Shao, Huazhe Xu:
Key-Grid: Unsupervised 3D Keypoints Detection using Grid Heatmap Features. - Ilias Diakonikolas, Daniel M. Kane, Mingchen Ma:
Active Learning of General Halfspaces: Label Queries vs Membership Queries. - Runlin Lei, Yuwei Hu, Yuchen Ren, Zhewei Wei:
Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level. - Ruizhe Zhong, Xingbo Du, Shixiong Kai, Zhentao Tang, Siyuan Xu, Jianye Hao, Mingxuan Yuan, Junchi Yan:
FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation. - Yichi Zhang, Yao Huang, Yitong Sun, Chang Liu, Zhe Zhao, Zhengwei Fang, Yifan Wang, Huanran Chen, Xiao Yang, Xingxing Wei, Hang Su, Yinpeng Dong, Jun Zhu:
MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models. - Yonggang Zhang, Jie Lu, Bo Peng, Zhen Fang, Yiu-ming Cheung:
Learning to Shape In-distribution Feature Space for Out-of-distribution Detection. - Jiaheng Liu, Zehao Ni, Haoran Que, Tao Sun, Noah Wang, Jian Yang, Jiakai Wang, Hongcheng Guo, Zhongyuan Peng, Ge Zhang, Jiayi Tian, Xingyuan Bu, Ke Xu, Wenge Rong, Junran Peng, Zhaoxiang Zhang:
RoleAgent: Building, Interacting, and Benchmarking High-quality Role-Playing Agents from Scripts. - François Cornet, Grigory Bartosh, Mikkel Schmidt, Christian Andersson Naesseth:
Equivariant Neural Diffusion for Molecule Generation. - Rongkun Zheng, Lu Qi, Xi Chen, Yi Wang, Kun Wang, Yu Qiao, Hengshuang Zhao:
SyncVIS: Synchronized Video Instance Segmentation. - Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg:
Gradients of Functions of Large Matrices. - Yuanpu Cao, Tianrong Zhang, Bochuan Cao, Ziyi Yin, Lu Lin, Fenglong Ma, Jinghui Chen:
Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization. - Alan Sun, Chiyu Ma, Kenneth Ge, Soroush Vosoughi:
Achieving Domain-Independent Certified Robustness via Knowledge Continuity. - Shukuan Wang, Ke Xue, Song Lei, Xiaobin Huang, Chao Qian:
Monte Carlo Tree Search based Space Transfer for Black Box Optimization. - Borja G. León, Francesco Riccio, Kaushik Subramanian, Peter R. Wurman, Peter Stone:
Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration. - Mohammad Hossein Bateni, Laxman Dhulipala, Willem Fletcher, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki:
Efficient Centroid-Linkage Clustering. - Keji He, Kehan Chen, Jiawang Bai, Yan Huang, Qi Wu, Shu-Tao Xia, Liang Wang:
Everyday Object Meets Vision-and-Language Navigation Agent via Backdoor. - Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, Pradeep Dasigi, Valentina Pyatkin, Abhilasha Ravichander, Sarah Wiegreffe, Nouha Dziri, Khyathi Raghavi Chandu, Jack Hessel, Yulia Tsvetkov, Noah A. Smith, Yejin Choi, Hanna Hajishirzi:
The Art of Saying No: Contextual Noncompliance in Language Models. - Josh Veitch-Michaelis, Andrew Cottam, Daniella Schweizer, Eben N. Broadbent, David Dao, Ce Zhang, Angelica Almeyda Zambrano, Simeon Max:
OAM-TCD: A globally diverse dataset of high-resolution tree cover maps. - Emily Silcock, Abhishek Arora, Luca D'Amico-Wong, Melissa Dell:
Newswire: A Large-Scale Structured Database of a Century of Historical News. - Xuanyu Zhang, Jiarui Meng, Runyi Li, Zhipei Xu, Yongbing Zhang, Jian Zhang:
GS-Hider: Hiding Messages into 3D Gaussian Splatting. - Qishuai Wen, Chun-Guang Li:
Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective. - Jiazuo Yu, Haomiao Xiong, Lu Zhang, Haiwen Diao, Yunzhi Zhuge, Lanqing Hong, Dong Wang, Huchuan Lu, You He, Long Chen:
LLMs Can Evolve Continually on Modality for X-Modal Reasoning. - Ziqi Zhou, Yufei Song, Minghui Li, Shengshan Hu, Xianlong Wang, Leo Yu Zhang, Dezhong Yao, Hai Jin:
DarkSAM: Fooling Segment Anything Model to Segment Nothing. - Zaijing Li, Yuquan Xie, Rui Shao, Gongwei Chen, Dongmei Jiang, Liqiang Nie:
Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks. - Xuefeng Liu, Fangfang Xia, Rick Stevens, Yuxin Chen:
Contextual Active Model Selection. - Raymond Chua, Arna Ghosh, Christos Kaplanis, Blake A. Richards, Doina Precup:
Learning Successor Features the Simple Way. - Fangyi Wang, Karthik Bharath, Oksana A. Chkrebtii, Sebastian Kurtek:
Probabilistic size-and-shape functional mixed models. - Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu:
Diffusion Models are Certifiably Robust Classifiers. - Tianyu Chen, Zhendong Wang, Mingyuan Zhou:
Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning. - Yen-Ju Lu, Jing Liu, Thomas Thebaud, Laureano Moro-Velázquez, Ariya Rastrow, Najim Dehak, Jesús Villalba:
CA-SSLR: Condition-Aware Self-Supervised Learning Representation for Generalized Speech Processing. - Chunhui Zhang, Li Liu, Guanjie Huang, Hao Wen, Xi Zhou, Yanfeng Wang:
WebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark. - Wenbo Hu, Zi-Yi Dou, Liunian Harold Li, Amita Kamath, Nanyun Peng, Kai-Wei Chang:
Matryoshka Query Transformer for Large Vision-Language Models. - Qinyi Chen, Jason Cheuk Nam Liang, Negin Golrezaei, Djallel Bouneffouf:
Interpolating Item and User Fairness in Multi-Sided Recommendations. - Jun Dan, Weiming Liu, Chunfeng Xie, Hua Yu, Shunjie Dong, Yanchao Tan:
TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering. - MyeongAh Cho, Taeoh Kim, Minho Shim, Dongyoon Wee, Sangyoun Lee:
Towards Multi-Domain Learning for Generalizable Video Anomaly Detection. - Guibin Zhang, Haonan Dong, Yuchen Zhang, Zhixun Li, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang:
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning. - Jehan Yang, Maxwell Soh, Vivianna Lieu, Douglas J. Weber, Zackory Erickson:
EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for Electromyography. - Dong Zhang, Zhaowei Li, Shimin Li, Xin Zhang, Pengyu Wang, Yaqian Zhou, Xipeng Qiu:
SpeechAlign: Aligning Speech Generation to Human Preferences. - Shengjun Zhang, Xin Fei, Fangfu Liu, Haixu Song, Yueqi Duan:
Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images. - Nicholas A. Dronen, Bardiya Akhbari, Manish Gawali:
SETLEXSEM CHALLENGE: Using Set Operations to Evaluate the Lexical and Semantic Robustness of Language Models. - Yang-Tian Sun, Yihua Huang, Lin Ma, Xiaoyang Lyu, Yan-Pei Cao, Xiaojuan Qi:
Splatter a Video: Video Gaussian Representation for Versatile Processing. - Danny Halawi, Fred Zhang, Chen Yueh-Han, Jacob Steinhardt:
Approaching Human-Level Forecasting with Language Models. - Momin Ahmad Khan, Yasra Chandio, Fatima M. Anwar:
HYDRA-FL: Hybrid Knowledge Distillation for Robust and Accurate Federated Learning. - Minjae Lee, Kyungmin Kim, Taesoo Kim, Sangdon Park:
Selective Generation for Controllable Language Models. - John Yang, Carlos E. Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, Ofir Press:
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering. - Qihan Ren, Junpeng Zhang, Yang Xu, Yue Xin, Dongrui Liu, Quanshi Zhang:
Towards the Dynamics of a DNN Learning Symbolic Interactions. - Zhihao Jia, Qi Pang, Trung Tran, David P. Woodruff, Zhihao Zhang, Wenting Zheng:
Communication Bounds for the Distributed Experts Problem. - Bargav Jayaraman, Chuan Guo, Kamalika Chaudhuri:
Déjà Vu Memorization in Vision-Language Models. - Jiamian Hu, Yuanyuan Hong, Yihua Chen, He Wang, Moriaki Yasuhara:
Noisy Ostracods: A Fine-Grained, Imbalanced Real-World Dataset for Benchmarking Robust Machine Learning and Label Correction Methods. - Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Shirui Pan:
ARC: A Generalist Graph Anomaly Detector with In-Context Learning. - Md Tanvirul Alam, Dipkamal Bhusal, Le Nguyen, Nidhi Rastogi:
CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence. - Haoyang Luo, Zheng Zhang, Yadan Luo:
Exploiting Descriptive Completeness Prior for Cross Modal Hashing with Incomplete Labels. - Shijie Ma, Fei Zhu, Zhun Zhong, Wenzhuo Liu, Xu-Yao Zhang, Chenglin Liu:
Happy: A Debiased Learning Framework for Continual Generalized Category Discovery. - Stephen Chung, Scott Niekum, David Krueger:
Predicting Future Actions of Reinforcement Learning Agents. - Ruiyuan Lyu, Jingli Lin, Tai Wang, Shuai Yang, Xiaohan Mao, Yilun Chen, Runsen Xu, Haifeng Huang, Chenming Zhu, Dahua Lin, Jiangmiao Pang:
MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations. - Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Ravi Hammond, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert T. Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster:
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Zheng Zhan, Zhenglun Kong, Yifan Gong, Yushu Wu, Zichong Meng, Hangyu Zheng, Xuan Shen, Stratis Ioannidis, Wei Niu, Pu Zhao, Yanzhi Wang:
Exploring Token Pruning in Vision State Space Models. - Bálint Mucsányi, Michael Kirchhof, Seong Joon Oh:
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks. - Quanwei Yang, Jiazhi Guan, Kaisiyuan Wang, Lingyun Yu, Wenqing Chu, Hang Zhou, ZhiQiang Feng, Haocheng Feng, Errui Ding, Jingdong Wang, Hongtao Xie:
ShowMaker: Creating High-Fidelity 2D Human Video via Fine-Grained Diffusion Modeling. - Yancheng Zhang, Mengxin Zheng, Yuzhang Shang, Xun Chen, Qian Lou:
HEPrune: Fast Private Training of Deep Neural Networks With Encrypted Data Pruning. - Marek Herde, Denis Huseljic, Lukas Rauch, Bernhard Sick:
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. - Zhiqing Sun, Longhui Yu, Yikang Shen, Weiyang Liu, Yiming Yang, Sean Welleck, Chuang Gan:
Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision. - Aneesh Muppidi, Zhiyu Zhang, Heng Yang:
Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning. - Eden Saig, Ohad Einav, Inbal Talgam-Cohen:
Incentivizing Quality Text Generation via Statistical Contracts. - Murad Tukan, Loay Mualem, Moran Feldman:
Practical 0.385-Approximation for Submodular Maximization Subject to a Cardinality Constraint. - Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran:
Fast Proxy Experiment Design for Causal Effect Identification. - Maorong Wang, Nicolas Michel, Jiafeng Mao, Toshihiko Yamasaki:
Dealing with Synthetic Data Contamination in Online Continual Learning. - Haosen Yang, Chuofan Ma, Bin Wen, Yi Jiang, Zehuan Yuan, Xiatian Zhu:
Recognize Any Regions. - Wanyun Xie, Thomas Pethick, Volkan Cevher:
SAMPa: Sharpness-aware Minimization Parallelized. - Jiahuan Cao, Yang Liu, Yongxin Shi, Kai Ding, Lianwen Jin:
WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts. - Zi-Hao Zhou, Siyuan Fang, Zi-Jing Zhou, Tong Wei, Yuanyu Wan, Min-Ling Zhang:
Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition. - Yixiu Mao, Qi Wang, Yun Qu, Yuhang Jiang, Xiangyang Ji:
Doubly Mild Generalization for Offline Reinforcement Learning. - Yang Dai, Oubo Ma, Longfei Zhang, Xingxing Liang, Shengchao Hu, Mengzhu Wang, Shouling Ji, Jincai Huang, Li Shen:
Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning? - Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao:
Calibrated Self-Rewarding Vision Language Models. - Yufei Wang, Zhihao Li, Lanqing Guo, Wenhan Yang, Alex C. Kot, Bihan Wen:
ContextGS : Compact 3D Gaussian Splatting with Anchor Level Context Model. - Yicheng Xu, Yuxin Chen, Jiahao Nie, Yusong Wang, Huiping Zhuang, Manabu Okumura:
Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Models. - Yueming Xu, Haochen Jiang, Zhongyang Xiao, Jianfeng Feng, Li Zhang:
DG-SLAM: Robust Dynamic Gaussian Splatting SLAM with Hybrid Pose Optimization. - Youngwan Lee, Kwanyong Park, Yoorhim Cho, Yong-Ju Lee, Sung Ju Hwang:
KOALA: Empirical Lessons Toward Memory-Efficient and Fast Diffusion Models for Text-to-Image Synthesis. - Zhao-Min Chen, Xin Jin, Yisu Ge, Sixian Chan:
In Pursuit of Causal Label Correlations for Multi-label Image Recognition. - Zixuan Gong, Guangyin Bao, Qi Zhang, Zhongwei Wan, Duoqian Miao, Shoujin Wang, Lei Zhu, Changwei Wang, Rongtao Xu, Liang Hu, Ke Liu, Yu Zhang:
NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction. - Vasilis Kontonis, Mingchen Ma, Christos Tzamos:
Active Classification with Few Queries under Misspecification. - Yufei Guo, Weihang Peng, Xiaode Liu, Yuanpei Chen, Yuhan Zhang, Xin Tong, Zhou Jie, Zhe Ma:
EnOF-SNN: Training Accurate Spiking Neural Networks via Enhancing the Output Feature. - Yuhui Zhang, Alyssa Unell, Xiaohan Wang, Dhruba Ghosh, Yuchang Su, Ludwig Schmidt, Serena Yeung:
Why are Visually-Grounded Language Models Bad at Image Classification? - Junlei Zhou, Jiashi Gao, Xiangyu Zhao, Xin Yao, Xuetao Wei:
Association of Objects May Engender Stereotypes: Mitigating Association-Engendered Stereotypes in Text-to-Image Generation. - Moritz Vandenhirtz, Sonia Laguna, Ricards Marcinkevics, Julia E. Vogt:
Stochastic Concept Bottleneck Models. - Oliver J. Sutton, Qinghua Zhou, Wei Wang, Desmond J. Higham, Alexander N. Gorban, Alexander Bastounis, Ivan Tyukin:
Stealth edits to large language models. - Alexander Soen, Hisham Husain, Philip Schulz, Vu Nguyen:
Rejection via Learning Density Ratios. - Mikael Møller Høgsgaard, Kasper Green Larsen, Markus Engelund Mathiasen:
The Many Faces of Optimal Weak-to-Strong Learning. - Jiacong Hu, Anda Cao, Zunlei Feng, Shengxuming Zhang, Yi Wang, Lingxiang Jia, Mingli Song:
Vision Mamba Mender. - Zhipan Xu, Lijun Zhang:
Online Non-convex Learning in Dynamic Environments. - Wei Tao, Yucheng Zhou, Yanlin Wang, Wenqiang Zhang, Hongyu Zhang, Yu Cheng:
MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution. - Yuchuan Tian, Zhijun Tu, Hanting Chen, Jie Hu, Chao Xu, Yunhe Wang:
U-DiTs: Downsample Tokens in U-Shaped Diffusion Transformers. - Zhitong Gao, Bingnan Li, Mathieu Salzmann, Xuming He:
Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts. - Tianbao Xie, Danyang Zhang, Jixuan Chen, Xiaochuan Li, Siheng Zhao, Ruisheng Cao, Toh Jing Hua, Zhoujun Cheng, Dongchan Shin, Fangyu Lei, Yitao Liu, Yiheng Xu, Shuyan Zhou, Silvio Savarese, Caiming Xiong, Victor Zhong, Tao Yu:
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments. - Axel Elaldi, Guido Gerig, Neel Dey:
Equivariant spatio-hemispherical networks for diffusion MRI deconvolution. - Daizong Liu, Mingyu Yang, Xiaoye Qu, Pan Zhou, Xiang Fang, Keke Tang, Yao Wan, Lichao Sun:
Pandora's Box: Towards Building Universal Attackers against Real-World Large Vision-Language Models. - Ziqiao Wang, Yongyi Mao:
Generalization Bounds via Conditional f-Information. - Zifan Wang, Yi Shen, Michael M. Zavlanos, Karl Henrik Johansson:
Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport. - Ui-Hyeop Shin, Sangyoun Lee, Taehan Kim, Hyung-Min Park:
Separate and Reconstruct: Asymmetric Encoder-Decoder for Speech Separation. - Hongbin Liu, Moyang Guo, Zhengyuan Jiang, Lun Wang, Neil Gong:
AudioMarkBench: Benchmarking Robustness of Audio Watermarking. - Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting:
DeiSAM: Segment Anything with Deictic Prompting. - Jiaqing Zhang, Mingxiang Cao, Weiying Xie, Jie Lei, Daixun Li, Wenbo Huang, Yunsong Li, Xue Yang:
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection. - Jin Li, Ziqiang He, Anwei Luo, Jian-Fang Hu, Z. Jane Wang, Xiangui Kang:
AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks. - Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, Drew Bagnell, Jason D. Lee, Wen Sun:
REBEL: Reinforcement Learning via Regressing Relative Rewards. - Ramy Mounir, Sudeep Sarkar:
Predictive Attractor Models. - Yicheng Li, Qian Lin:
Improving Adaptivity via Over-Parameterization in Sequence Models. - Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, Qianhui Wu, Xufang Luo, Surin Ahn, Zhenhua Han, Amir Abdi, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, Lili Qiu:
MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention. - Sriyash Poddar, Yanming Wan, Hamish Ivison, Abhishek Gupta, Natasha Jaques:
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning. - Haiwen Diao, Yufeng Cui, Xiaotong Li, Yueze Wang, Huchuan Lu, Xinlong Wang:
Unveiling Encoder-Free Vision-Language Models. - Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue (Steve) Liu, Craig Boutilier, Maryam Karimzadehgan:
Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval. - Xinyu Yang, Yu Sun, Xiaojie Yuan, Xinyang Chen:
Frequency-aware Generative Models for Multivariate Time Series Imputation. - Marko Medvedev, Gal Vardi, Nati Srebro:
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality. - Hang Zhang, Jiawei Sun, Renqi Chen, Wei Liu, Zhonghang Yuan, Xinzhe Zheng, Zhefan Wang, Zhiyuan Yang, Hang Yan, Han-Sen Zhong, Xiqing Wang, Wanli Ouyang, Fan Yang, Nanqing Dong:
Empowering and Assessing the Utility of Large Language Models in Crop Science. - Ye Tian, Baolin Peng, Linfeng Song, Lifeng Jin, Dian Yu, Lei Han, Haitao Mi, Dong Yu:
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing. - Steve Hanneke, Hongao Wang:
A Theory of Optimistically Universal Online Learnability for General Concept Classes. - Daniel Bramblett, Siddharth Srivastava:
Belief-State Query Policies for User-Aligned POMDPs. - Honghao Wei, Xiyue Peng, Arnob Ghosh, Xin Liu:
Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning. - Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations. - Sirui Xu, Ziyin Wang, Yu-Xiong Wang, Liangyan Gui:
InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction. - Jeongwhan Choi, Hyowon Wi, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, Noseong Park:
Graph Convolutions Enrich the Self-Attention in Transformers! - Gong Zhang, Kihyuk Sohn, Meera Hahn, Humphrey Shi, Irfan Essa:
FineStyle: Fine-grained Controllable Style Personalization for Text-to-image Models. - Jianwei Zheng, Wei Li, Ni Xu, Junwei Zhu, Xiaoxu Lin, Xiaoqin Zhang:
Alias-Free Mamba Neural Operator. - Tero Karras, Miika Aittala, Tuomas Kynkäänniemi, Jaakko Lehtinen, Timo Aila, Samuli Laine:
Guiding a Diffusion Model with a Bad Version of Itself. - James Oldfield, Markos Georgopoulos, Grigorios Chrysos, Christos Tzelepis, Yannis Panagakis, Mihalis Nicolaou, Jiankang Deng, Ioannis Patras:
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization. - Jio Oh, Soyeon Kim, Junseok Seo, Jindong Wang, Ruochen Xu, Xing Xie, Steven Whang:
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models. - Top Piriyakulkij, Cassidy Langenfeld, Tuan Anh Le, Kevin Ellis:
Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning. - Zhengxiao Du, Aohan Zeng, Yuxiao Dong, Jie Tang:
Understanding Emergent Abilities of Language Models from the Loss Perspective. - Keshigeyan Chandrasegaran, Agrim Gupta, Lea M. Hadzic, Taran Kota, Jimming He, Cristóbal Eyzaguirre, Zane Durante, Manling Li, Jiajun Wu, Li Fei-Fei:
HourVideo: 1-Hour Video-Language Understanding. - Pengyue Jia, Yiding Liu, Xiaopeng Li, Xiangyu Zhao, Yuhao Wang, Yantong Du, Xiao Han, Xuetao Wei, Shuaiqiang Wang, Dawei Yin:
G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models. - Yunchao Liu, Ha Dong, Xin Wang, Rocco Moretti, Yu Wang, Zhaoqian Su, Jiawei Gu, Bobby Bodenheimer, Charles David Weaver, Jens Meiler, Tyler Derr:
WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking. - Bowen Yuan, Zijian Wang, Mahsa Baktashmotlagh, Yadan Luo, Zi Huang:
Color-Oriented Redundancy Reduction in Dataset Distillation. - Brett Leroux, Luis Rademacher:
Euclidean distance compression via deep random features. - Desai Xie, Sai Bi, Zhixin Shu, Kai Zhang, Zexiang Xu, Yi Zhou, Sören Pirk, Arie E. Kaufman, Xin Sun, Hao Tan:
LRM-Zero: Training Large Reconstruction Models with Synthesized Data. - Kangning Liu, Brian L. Price, Jason Kuen, Yifei Fan, Zijun Wei, Luis Figueroa, Krzysztof J. Geras, Carlos Fernandez-Granda:
Uncertainty-aware Fine-tuning of Segmentation Foundation Models. - Antoine Picard-Weibel, Roman Moscoviz, Benjamin Guedj:
Learning via Surrogate PAC-Bayes. - Bin Lei, Yi Zhang, Shan Zuo, Ali Payani, Caiwen Ding:
MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems. - Wei Dong, Han Zhou, Yulun Zhang, Xiaohong Liu, Jun Chen:
ECMamba: Consolidating Selective State Space Model with Retinex Guidance for Efficient Multiple Exposure Correction. - Itamar Harel, William Hoza, Gal Vardi, Itay Evron, Nati Srebro, Daniel Soudry:
Provable Tempered Overfitting of Minimal Nets and Typical Nets. - Rui Ai, David Simchi-Levi, Feng Zhu:
Dynamic Service Fee Pricing under Strategic Behavior: Actions as Instruments and Phase Transition. - Hangyu Zhou, Chia-Hsiang Kao, Cheng Perng Phoo, Utkarsh Mall, Bharath Hariharan, Kavita Bala:
AllClear: A Comprehensive Dataset and Benchmark for Cloud Removal in Satellite Imagery. - Zenan Li, Yifan Wu, Zhaoyu Li, Xinming Wei, Xian Zhang, Fan Yang, Xiaoxing Ma:
Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistency. - Eshta Bhardwaj, Harshit Gujral, Siyi Wu, Ciara Zogheib, Tegan Maharaj, Christoph Becker:
The State of Data Curation at NeurIPS: An Assessment of Dataset Development Practices in the Datasets and Benchmarks Track. - Francesco Innocenti, El Mehdi Achour, Ryan Singh, Christopher L. Buckley:
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks? - Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Christian Schröder de Witt:
Unelicitable Backdoors via Cryptographic Transformer Circuits. - Yiran Zhao, Wenyue Zheng, Tianle Cai, Do Xuan Long, Kenji Kawaguchi, Anirudh Goyal, Michael Qizhe Shieh:
Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling. - Shuangpeng Han, Ziyu Wang, Mengmi Zhang:
Flow Snapshot Neurons in Action: Deep Neural Networks Generalize to Biological Motion Perception. - Peng Wang, Zexi Li, Ningyu Zhang, Ziwen Xu, Yunzhi Yao, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen:
WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models. - Guillaume Jaume, Paul Doucet, Andrew H. Song, Ming Yang Lu, Cristina Almagro-Pérez, Sophia J. Wagner, Anurag Vaidya, Richard J. Chen, Drew F. K. Williamson, Ahrong Kim, Faisal Mahmood:
HEST-1k: A Dataset For Spatial Transcriptomics and Histology Image Analysis. - Miklós Z. Rácz, Jifan Zhang:
Harnessing Multiple Correlated Networks for Exact Community Recovery. - Syrine Belakaria, Ben Letham, Jana Doppa, Barbara Engelhardt, Stefano Ermon, Eytan Bakshy:
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes. - Zaixi Zhang, Mengdi Wang, Qi Liu:
FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling. - Shutong Ding, Ke Hu, Zhenhao Zhang, Kan Ren, Weinan Zhang, Jingyi Yu, Jingya Wang, Ye Shi:
Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization. - Mikhail Mozikov, Nikita Severin, Valeria Bodishtianu, Maria Glushanina, Ivan Nasonov, Daniil Orekhov, Pekhotin Vladislav, Ivan Makovetskiy, Mikhail Baklashkin, Vasily Lavrentyev, Akim Tsvigun, Denis Turdakov, Tatiana Shavrina, Andrey V. Savchenko, Ilya Makarov:
EAI: Emotional Decision-Making of LLMs in Strategic Games and Ethical Dilemmas. - Yiming Lei, Zilong Li, Junping Zhang, Hongming Shan:
Denoising Diffusion Path: Attribution Noise Reduction with An Auxiliary Diffusion Model. - Jiacong Hu, Hao Chen, Kejia Chen, Yang Gao, Jingwen Ye, Xingen Wang, Mingli Song, Zunlei Feng:
Transformer Doctor: Diagnosing and Treating Vision Transformers. - Yi-Chung Chen, Zhi-Kai Huang, Jing-Ren Chen:
StepbaQ: Stepping backward as Correction for Quantized Diffusion Models. - Dong Hoon Lee, Seunghoon Hong:
Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers. - Kaidong Zhang, Pengzhen Ren, Bingqian Lin, Junfan Lin, Shikui Ma, Hang Xu, Xiaodan Liang:
PIVOT-R: Primitive-Driven Waypoint-Aware World Model for Robotic Manipulation. - Michael Galkin, Jincheng Zhou, Bruno Ribeiro, Jian Tang, Zhaocheng Zhu:
A Foundation Model for Zero-shot Logical Query Reasoning. - Xiaonan Nie, Qibin Liu, Fangcheng Fu, Shenhan Zhu, Xupeng Miao, Xiaoyang Li, Yang Zhang, Shouda Liu, Bin Cui:
LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing. - Yinuo Wang, Likun Wang, Yuxuan Jiang, Wenjun Zou, Tong Liu, Xujie Song, Wenxuan Wang, Liming Xiao, Jiang Wu, Jingliang Duan, Shengbo Li:
Diffusion Actor-Critic with Entropy Regulator. - Yinlin Deng, Chunqiu Steven Xia, Zhezhen Cao, Meiziniu Li, Lingming Zhang:
Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs? - Alexander Tyurin, Kaja Gruntkowska, Peter Richtárik:
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations. - Vincent Zhihao Zheng, Lijun Sun:
Multivariate Probabilistic Time Series Forecasting with Correlated Errors. - Qingyuan Wu, Simon Sinong Zhan, Yixuan Wang, Yuhui Wang, Chung-Wei Lin, Chen Lv, Qi Zhu, Chao Huang:
Variational Delayed Policy Optimization. - Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu:
MILP-StuDio: MILP Instance Generation via Block Structure Decomposition. - David Mayo, Christopher Wang, Asa Harbin, Abdulrahman Alabdulkareem, Albert E. Shaw, Boris Katz, Andrei Barbu:
BrainBits: How Much of the Brain are Generative Reconstruction Methods Using? - Jing Zhang, Linjiajie Fang, Kexin Shi, Wenjia Wang, Bingyi Jing:
Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model. - Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley Kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh R. N., Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong:
APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets. - Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang:
ChatCam: Empowering Camera Control through Conversational AI. - Yiting Chen, Junchi Yan:
What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information. - Yuhang Yang, Wei Zhai, Chengfeng Wang, Chengjun Yu, Yang Cao, Zheng-Jun Zha:
EgoChoir: Capturing 3D Human-Object Interaction Regions from Egocentric Views. - Hao-Lun Sun, Lei Hsiung, Nandhini Chandramoorthy, Pin-Yu Chen, Tsung-Yi Ho:
NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes. - Xu Pan, Aaron Philip, Ziqian Xie, Odelia Schwartz:
Dissecting Query-Key Interaction in Vision Transformers. - Chengyang Ying, Zhongkai Hao, Xinning Zhou, Xuezhou Xu, Hang Su, Xingxing Zhang, Jun Zhu:
PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning. - Yehu Chen, Muchen Xi, Joshua Jackson, Jacob M. Montgomery, Roman Garnett:
Idiographic Personality Gaussian Process for Psychological Assessment. - Jiaqi Wang, Qi Li, Lingjuan Lyu, Fenglong Ma:
pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning. - Firas Trabelsi, David Vilar, Mara Finkelstein, Markus Freitag:
Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms. - Kiran Lekkala, Henghui Bao, Peixu Cai, Wei Lim, Chen Liu, Laurent Itti:
USCILab3D: A Large-scale, Long-term, Semantically Annotated Outdoor Dataset. - Xiaohang Xu, Renhe Jiang, Chuang Yang, Zipei Fan, Kaoru Sezaki:
Taming the Long Tail in Human Mobility Prediction. - Zhenbang Wu, Anant Dadu, Mike A. Nalls, Faraz Faghri, Jimeng Sun:
Instruction Tuning Large Language Models to Understand Electronic Health Records. - Chaoran Cheng, Jiahan Li, Jian Peng, Ge Liu:
Categorical Flow Matching on Statistical Manifolds. - Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli:
How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach. - Qiguang Chen, Libo Qin, Jiaqi Wang, Jingxuan Zhou, Wanxiang Che:
Unlocking the Capabilities of Thought: A Reasoning Boundary Framework to Quantify and Optimize Chain-of-Thought. - Shaowen Wang, Linxi Yu, Jian Li:
LoRA-GA: Low-Rank Adaptation with Gradient Approximation. - Xiaohan Lin, Qingxing Cao, Yinya Huang, Haiming Wang, Jianqiao Lu, Zhengying Liu, Linqi Song, Xiaodan Liang:
FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving. - Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu:
DALD: Improving Logits-based Detector without Logits from Black-box LLMs. - Mengmeng Chen, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew Soon Ong, Qiqi Liu, Qicheng Lao, Han Yu:
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning. - Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong:
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. - Songkai Xue, Yuekai Sun:
Distributionally Robust Performative Prediction. - Pulkit Gopalani, Ekdeep Singh Lubana, Wei Hu:
Abrupt Learning in Transformers: A Case Study on Matrix Completion. - Haoqi Yuan, Yuhui Fu, Feiyang Xie, Zongqing Lu:
Pre-Trained Multi-Goal Transformers with Prompt Optimization for Efficient Online Adaptation. - Kun Yi, Jingru Fei, Qi Zhang, Hui He, Shufeng Hao, Defu Lian, Wei Fan:
FilterNet: Harnessing Frequency Filters for Time Series Forecasting. - Benyuan Meng, Qianqian Xu, Zitai Wang, Xiaochun Cao, Qingming Huang:
Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features. - Seunggeun Chi, Pin-Hao Huang, Enna Sachdeva, Hengbo Ma, Karthik Ramani, Kwonjoon Lee:
Estimating Ego-Body Pose from Doubly Sparse Egocentric Video Data. - Qian Chen, Ling Chen:
DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach. - Qiming Hu, Hainuo Wang, Xiaojie Guo:
Single Image Reflection Separation via Dual-Stream Interactive Transformers. - Yuxiao Qu, Tianjun Zhang, Naman Garg, Aviral Kumar:
Recursive Introspection: Teaching Language Model Agents How to Self-Improve. - Jintao Guo, Lei Qi, Yinghuan Shi, Yang Gao:
START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation. - Shobhita Sundaram, Stephanie Fu, Lukas Muttenthaler, Netanel Tamir, Lucy Chai, Simon Kornblith, Trevor Darrell, Phillip Isola:
When does perceptual alignment benefit vision representations? - Mingyang Yi, Aoxue Li, Yi Xin, Zhenguo Li:
Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model. - Zhengmian Hu, Heng Huang:
Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models. - Minghao Zhu, Zhengpu Wang, Mengxian Hu, Ronghao Dang, Xiao Lin, Xun Zhou, Chengju Liu, Qijun Chen:
MoTE: Reconciling Generalization with Specialization for Visual-Language to Video Knowledge Transfer. - Hui Ye, Rajshekhar Sunderraman, Jonathan Shihao Ji:
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles. - Yuang Ai, Xiaoqiang Zhou, Huaibo Huang, Xiaotian Han, Zhengyu Chen, Quanzeng You, Hongxia Yang:
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation. - Meng Ding, Mingxi Lei, Liyang Zhu, Shaowei Wang, Di Wang, Jinhui Xu:
Revisiting Differentially Private ReLU Regression. - Ronast Subedi, Lu Wei, Wenhan Gao, Shayok Chakraborty, Yi Liu:
Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism. - Mathieu Tanneau, Pascal Van Hentenryck:
Dual Lagrangian Learning for Conic Optimization. - Lucas Monteiro Paes, Dennis Wei, Flávio P. Calmon:
Selective Explanations. - Dimitrios Bachtis, Giulio Biroli, Aurélien Decelle, Beatriz Seoane:
Cascade of phase transitions in the training of energy-based models. - Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu:
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. - Quoc Tran-Dinh, Trang H. Tran, Lam M. Nguyen:
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization. - Petrus Mikkola, Luigi Acerbi, Arto Klami:
Preferential Normalizing Flows. - Sasha Salter, Richard Warren, Collin Schlager, Adrian Spurr, Shangchen Han, Rohin Bhasin, Yujun Cai, Peter Walkington, Anuoluwapo Bolarinwa, Robert J. Wang, Nathan Danielson, Josh Merel, Eftychios A. Pnevmatikakis, Jesse Marshall:
emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation. - Chiyu Max Jiang, Yijing Bai, Andre Cornman, Christopher Davis, Xiukun Huang, Hong Jeon, Sakshum Kulshrestha, John Lambert, Shuangyu Li, Xuanyu Zhou, Carlos Fuertes, Chang Yuan, Mingxing Tan, Yin Zhou, Dragomir Anguelov:
SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout. - Chubin Zhang, Hongliang Song, Yi Wei, Chen Yu, Jiwen Lu, Yansong Tang:
GeoLRM: Geometry-Aware Large Reconstruction Model for High-Quality 3D Gaussian Generation. - Shayan Shekarforoush, David B. Lindell, Marcus A. Brubaker, David J. Fleet:
CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference. - Junqiang Huang, Zhaojun Guo, Ge Luo, Zhenxing Qian, Sheng Li, Xinpeng Zhang:
Disentangled Style Domain for Implicit z-Watermark Towards Copyright Protection. - Qinqian Lei, Bo Wang, Robby T. Tan:
EZ-HOI: VLM Adaptation via Guided Prompt Learning for Zero-Shot HOI Detection. - Long-Fei Li, Peng Zhao, Zhi-Hua Zhou:
Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs. - Vinod Raman, Ambuj Tewari:
Online Classification with Predictions. - Mohammad ShahverdiKondori, Ehsan Mokhtarian, Negar Kiyavash:
QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs. - Haoyu Zhang, Wenbin Wang, Tianshu Yu:
Towards Robust Multimodal Sentiment Analysis with Incomplete Data. - Peng Li, Yuan Liu, Xiaoxiao Long, Feihu Zhang, Cheng Lin, Mengfei Li, Xingqun Qi, Shanghang Zhang, Wei Xue, Wenhan Luo, Ping Tan, Wenping Wang, Qifeng Liu, Yike Guo:
Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention. - Xilin Zhang, Wang Chi Cheung:
Piecewise-Stationary Bandits with Knapsacks. - Sangwon Jung, Sumin Yu, Sanghyuk Chun, Taesup Moon:
Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? - A Theoretical and Empirical Study. - Tong Zhou, Xuandong Zhao, Xiaolin Xu, Shaolei Ren:
Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature. - Takanori Maehara, Hoang NT:
Deep Homomorphism Networks. - Marah Ghoummaid, Uri Shalit:
When to Act and When to Ask: Policy Learning With Deferral Under Hidden Confounding. - Chen-Hao Chao, Chien Feng, Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee:
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow. - Jingfeng Yao, Cheng Wang, Wenyu Liu, Xinggang Wang:
FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification. - Harshavardhan Kamarthi, B. Aditya Prakash:
Large Pre-trained time series models for cross-domain Time series analysis tasks. - Yi Ma, Jianye Hao, Xiaohan Hu, Yan Zheng, Chenjun Xiao:
Iteratively Refined Behavior Regularization for Offline Reinforcement Learning. - Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter:
Rethinking LLM Memorization through the Lens of Adversarial Compression. - Thanh Nguyen-Tang, Raman Arora:
Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms. - Qizhen (Irene) Zhang, Nikolas Gritsch, Dwaraknath Gnaneshwar, Simon Guo, David Cairuz, Bharat Venkitesh, Jakob N. Foerster, Phil Blunsom, Sebastian Ruder, Ahmet Üstün, Acyr Locatelli:
BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts. - Geng Yu, Jianing Zhu, Jiangchao Yao, Bo Han:
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection. - Tong Wu, Yanpeng Zhao, Zilong Zheng:
An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding. - Prakhar Srivastava, Ruihan Yang, Gavin Kerrigan, Gideon Dresdner, Jeremy McGibbon, Christopher S. Bretherton, Stephan Mandt:
Precipitation Downscaling with Spatiotemporal Video Diffusion. - Rujikorn Charakorn, Poramate Manoonpong, Nat Dilokthanakul:
Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners. - Tianhong Li, Yonglong Tian, He Li, Mingyang Deng, Kaiming He:
Autoregressive Image Generation without Vector Quantization. - Hadley Black, Euiwoong Lee, Arya Mazumdar, Barna Saha:
Clustering with Non-adaptive Subset Queries. - Md Yousuf Harun, Kyungbok Lee, Gianmarco J. Gallardo, Giri Krishnan, Christopher Kanan:
What Variables Affect Out-of-Distribution Generalization in Pretrained Models? - Rafael Oliveira, Dino Sejdinovic, David Howard, Edwin V. Bonilla:
Bayesian Adaptive Calibration and Optimal Design. - Gantavya Bhatt, Arnav Das, Jeff A. Bilmes:
Deep Submodular Peripteral Networks. - Jules Berman, Tobias Blickhan, Benjamin Peherstorfer:
Parametric model reduction of mean-field and stochastic systems via higher-order action matching. - Yang Yue, Yulin Wang, Bingyi Kang, Yizeng Han, Shenzhi Wang, Shiji Song, Jiashi Feng, Gao Huang:
DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution. - Pei Yang, Hai Ci, Yiren Song, Mike Zheng Shou:
Can Simple Averaging Defeat Modern Watermarks? - Kulin Shah, Nishanth Dikkala, Xin Wang, Rina Panigrahy:
Causal language modeling can elicit search and reasoning capabilities on logic puzzles. - Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko:
Local and Adaptive Mirror Descents in Extensive-Form Games. - Quanqi Hu, Qi Qi, Zhaosong Lu, Tianbao Yang:
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions. - Jaewoo Lee, Sujin Yun, Taeyoung Yun, Jinkyoo Park:
GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning. - Dongchao Yang, Haohan Guo, Yuanyuan Wang, Rongjie Huang, Xiang Li, Xu Tan, Xixin Wu, Helen Meng:
UniAudio 1.5: Large Language Model-Driven Audio Codec is A Few-Shot Audio Task Learner. - Jiawei Ren, Cheng Xie, Ashkan Mirzaei, Hanxue Liang, Xiaohui Zeng, Karsten Kreis, Ziwei Liu, Antonio Torralba, Sanja Fidler, Seung Wook Kim, Huan Ling:
L4GM: Large 4D Gaussian Reconstruction Model. - Zhenyu Wang, Yali Li, Hengshuang Zhao, Shengjin Wang:
One for All: Multi-Domain Joint Training for Point Cloud Based 3D Object Detection. - Yanpeng Ye, Jie Ren, Shaozhou Wang, Yuwei Wan, Imran Razzak, Bram Hoex, Haofen Wang, Tong Xie, Wenjie Zhang:
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model. - Junyi Ao, Yuancheng Wang, Xiaohai Tian, Dekun Chen, Jun Zhang, Lu Lu, Yuxuan Wang, Haizhou Li, Zhizheng Wu:
SD-Eval: A Benchmark Dataset for Spoken Dialogue Understanding Beyond Words. - Adriel Saporta, Aahlad Manas Puli, Mark Goldstein, Rajesh Ranganath:
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities. - Yifu Qiu, Zheng Zhao, Yftah Ziser, Anna Korhonen, Edoardo Maria Ponti, Shay B. Cohen:
Spectral Editing of Activations for Large Language Model Alignment. - Axel Levy, Rishwanth Raghu, David Shustin, Adele Rui-Yang Peng, Huan Li, Oliver Biggs Clarke, Gordon Wetzstein, Ellen D. Zhong:
Mixture of neural fields for heterogeneous reconstruction in cryo-EM. - Rui Pan, Xiang Liu, Shizhe Diao, Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang:
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning. - Suyoung Lee, Jaeyoung Chung, Jaeyoo Huh, Kyoung Mu Lee:
ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings. - Hiroki Furuta, Kuang-Huei Lee, Shixiang Shane Gu, Yutaka Matsuo, Aleksandra Faust, Heiga Zen, Izzeddin Gur:
Geometric-Averaged Preference Optimization for Soft Preference Labels. - Chenyi Zhuang, Ying Hu, Pan Gao:
Magnet: We Never Know How Text-to-Image Diffusion Models Work, Until We Learn How Vision-Language Models Function. - Yuankai Luo, Hongkang Li, Lei Shi, Xiao-Ming Wu:
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding. - Giangiacomo Mercatali, André Freitas, Jie Chen:
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series. - Hao Fei, Shengqiong Wu, Hanwang Zhang, Tat-Seng Chua, Shuicheng Yan:
Vitron: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing. - Dongjie Yang, Suyuan Huang, Chengqiang Lu, Xiaodong Han, Haoxin Zhang, Yan Gao, Yao Hu, Hai Zhao:
Vript: A Video Is Worth Thousands of Words. - Mishaal Kazmi, Hadrien Lautraite, Alireza Akbari, Qiaoyue Tang, Mauricio Soroco, Tao Wang, Sébastien Gambs, Mathias Lécuyer:
PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining. - Jake Snell, Gianluca M. Bencomo, Tom Griffiths:
A Metalearned Neural Circuit for Nonparametric Bayesian Inference. - Le Zhang, Jiayang Chen, Tao Shen, Yu Li, Siqi Sun:
MSA Generation with Seqs2Seqs Pretraining: Advancing Protein Structure Predictions. - Ben Finkelshtein, Ismail Ilkan Ceylan, Michael M. Bronstein, Ron Levie:
Learning on Large Graphs using Intersecting Communities. - Yasi Zhang, Peiyu Yu, Yaxuan Zhu, Yingshan Chang, Feng Gao, Ying Nian Wu, Oscar Leong:
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching. - Taihei Oki, Shinsaku Sakaue:
No-Regret M♮-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting. - Michal Junczyk:
BIGOS V2 Benchmark for Polish ASR: Curated Datasets and Tools for Reproducible Evaluation. - Minghao Shao, Sofija Jancheska, Meet Udeshi, Brendan Dolan-Gavitt, Haoran Xi, Kimberly Milner, Boyuan Chen, Max Yin, Siddharth Garg, Prashanth Krishnamurthy, Farshad Khorrami, Ramesh Karri, Muhammad Shafique:
NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security. - Xiang Li, Yixiang Dai, Qing Qu:
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure. - Jiahe Chen, Jinkun Cao, Dahua Lin, Kris Kitani, Jiangmiao Pang:
MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction. - Zuowen Wang, Longbiao Cheng, Pehuen Moure, Niklas Hahn, Shih-Chii Liu:
DeltaDEQ: Exploiting Heterogeneous Convergence for Accelerating Deep Equilibrium Iterations. - Huaqing Zhang, Lesi Chen, Jing Xu, Jingzhao Zhang:
Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem. - Jia Li, Ge Li, Xuanming Zhang, Yunfei Zhao, Yihong Dong, Zhi Jin, Binhua Li, Fei Huang, Yongbin Li:
EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations. - Xuangeng Chu, Tatsuya Harada:
Generalizable and Animatable Gaussian Head Avatar. - Mengxiao Zhang, Ramiro Deo-Campo Vuong, Haipeng Luo:
No-Regret Learning for Fair Multi-Agent Social Welfare Optimization. - Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie H. Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel:
Initializing Services in Interactive ML Systems for Diverse Users. - Yuancheng Xu, Jiarui Yao, Manli Shu, Yanchao Sun, Zichu Wu, Ning Yu, Tom Goldstein, Furong Huang:
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models. - Yiming Wang, Kaiyan Zhao, Furui Liu, Leong Hou U:
Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus. - Genki Osada, Makoto Shing, Takashi Nishide:
Local Curvature Smoothing with Stein's Identity for Efficient Score Matching. - Cheng Chen, Junchen Zhu, Xu Luo, Hengtao Shen, Jingkuan Song, Lianli Gao:
CoIN: A Benchmark of Continual Instruction Tuning for Multimodel Large Language Models. - Eirini Angeloudi, Jeroen Audenaert, Micah Bowles, Benjamin M. Boyd, David Chemaly, Brian Cherinka, Ioana Ciuca, Miles D. Cranmer, Aaron Do, Matthew Grayling, Erin E. Hayes, Tom Hehir, Shirley Ho, Marc Huertas-Company, Kartheik Iyer, Maja Jablonska, François Lanusse, Henry Leung, Kaisey Mandel, Rafael Martínez-Galarza, Peter Melchior, Lucas Meyer, Liam Holden Parker, Helen Qu, Jeff Shen, Michael J. Smith, Connor Stone, Mike Walmsley, John F. Wu:
The Multimodal Universe: Enabling Large-Scale Machine Learning with 100 TB of Astronomical Scientific Data. - Chaoyi Pan, Zeji Yi, Guanya Shi, Guannan Qu:
Model-based Diffusion for Trajectory Optimization. - Chieh-Yun Chen, Chiang Tseng, Li-Wu Tsao, Hong-Han Shuai:
A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization. - Zichen Tian, Zhaozheng Chen, Qianru Sun:
Learning De-Biased Representations for Remote-Sensing Imagery. - Fedor Velikonivtsev, Mikhail Mironov, Liudmila Prokhorenkova:
Challenges of Generating Structurally Diverse Graphs. - Nikolaos Tsilivis, Natalie Frank, Nati Srebro, Julia Kempe:
The Price of Implicit Bias in Adversarially Robust Generalization. - Jiayu Qin, Jian Chen, Rohan Sharma, Jingchen Sun, Changyou Chen:
A probability contrastive learning framework for 3D molecular representation learning. - Yasin Abbasi-Yadkori, Ilja Kuzborskij, András György, Csaba Szepesvári:
To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty. - Xinlei Wang, Maike Feng, Jing Qiu, Jinjin Gu, Junhua Zhao:
From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection. - Tong Wei, Hao-Tian Li, Chun-Shu Li, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang:
Vision-Language Models are Strong Noisy Label Detectors. - Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Sercan Ö. Arik:
Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization. - Anson Ho, Tamay Besiroglu, Ege Erdil, Zifan Carl Guo, David Owen, Robi Rahman, David Atkinson, Neil Thompson, Jaime Sevilla:
Algorithmic progress in language models. - Yeongbin Seo, Dongha Lee, Jinyoung Yeo:
Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning. - Weida Li, Yaoliang Yu:
One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently. - Xinrui Wang, Chuanxing Geng, Wenhai Wan, Shao-Yuan Li, Songcan Chen:
Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning. - Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas:
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models. - Hengfu Yu, Jinhong Deng, Wen Li, Lixin Duan:
Towards Unsupervised Model Selection for Domain Adaptive Object Detection. - Ildus Sadrtdinov, Maxim Kodryan, Eduard Pokonechny, Ekaterina Lobacheva, Dmitry P. Vetrov:
Where Do Large Learning Rates Lead Us? - Gagan Jain, Nidhi Hegde, Aditya Kusupati, Arsha Nagrani, Shyamal Buch, Prateek Jain, Anurag Arnab, Sujoy Paul:
Mixture of Nested Experts: Adaptive Processing of Visual Tokens. - Gyusam Chang, Jiwon Lee, Donghyun Kim, Jinkyu Kim, Dongwook Lee, Daehyun Ji, Sujin Jang, Sangpil Kim:
Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection. - Mehreen Saeed, Adrian Chan, Anupam Mijar, Joseph Moukarzel, Georges Habchi, Carlos Younes, Amin Elias, Chau-Wai Wong, Akram Khater:
Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition. - Long-Fei Li, Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou:
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation. - Xiaoning Wang, Yuyang Huo, Liuhua Peng, Changliang Zou:
Conformalized Multiple Testing after Data-dependent Selection. - Yuseung Lee, Taehoon Yoon, Minhyuk Sung:
GrounDiT: Grounding Diffusion Transformers via Noisy Patch Transplantation. - Ren Li, Corentin Dumery, Zhantao Deng, Pascal Fua:
Reconstruction of Manipulated Garment with Guided Deformation Prior. - Guanghao Wei, Yining Huang, Chenru Duan, Yue Song, Yuanqi Du:
Navigating Chemical Space with Latent Flows. - Chang Liu, Rebecca Saul, Yihao Sun, Edward Raff, Maya Fuchs, Townsend Southard Pantano, James Holt, Kristopher K. Micinski:
Assemblage: Automatic Binary Dataset Construction for Machine Learning. - Jason D. Lee, Kazusato Oko, Taiji Suzuki, Denny Wu:
Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit. - Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos J. Storkey, Tim Pearce, François Fleuret:
Diffusion for World Modeling: Visual Details Matter in Atari. - Yusuke Kuwana, Yuta Goto, Takashi Shibata, Go Irie:
Black-Box Forgetting. - Ari S. Benjamin, Christian-Gernot Pehle, Kyle Daruwalla:
Continual learning with the neural tangent ensemble. - Shentong Mo, Yibing Song:
Aligning Audio-Visual Joint Representations with an Agentic Workflow. - Jing Yao, Xiaoyuan Yi, Xing Xie:
CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses. - Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine:
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. - Jeongwoo Shin, Inseo Lee, Junho Lee, Joonseok Lee:
Self-Guided Masked Autoencoder. - Yuanchen Wu, Yubai Yuan:
Robust Offline Active Learning on Graphs. - Qing Zhong, Guodong Ding, Angela Yao:
OnlineTAS: An Online Baseline for Temporal Action Segmentation. - Yichao Fu, Siqi Zhu, Runlong Su, Aurick Qiao, Ion Stoica, Hao Zhang:
Efficient LLM Scheduling by Learning to Rank. - Jiawei Yao, Chuming Li, Canran Xiao:
Swift Sampler: Efficient Learning of Sampler by 10 Parameters. - Yuanyuan Wang, Biwei Huang, Wei Huang, Xi Geng, Mingming Gong:
Identifiability Analysis of Linear ODE Systems with Hidden Confounders. - Jingyang Yuan, Gongbo Sun, Zhiping Xiao, Hang Zhou, Xiao Luo, Junyu Luo, Yusheng Zhao, Wei Ju, Ming Zhang:
EGODE: An Event-attended Graph ODE Framework for Modeling Rigid Dynamics. - Robert C. Garrett, Trevor Harris, Zhuo Wang, Bo Li:
Validating Climate Models with Spherical Convolutional Wasserstein Distance. - Ilker Oguz, Niyazi Ulas Dinç, Mustafa Yildirim, Junjie Ke, Innfarn Yoo, Qifei Wang, Feng Yang, Christophe Moser, Demetri Psaltis:
Optical Diffusion Models for Image Generation. - Hilal Asi, Daogao Liu, Kevin Tian:
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions. - Hongbo Zhao, Lue Fan, Yuntao Chen, Haochen Wang, yuran Yang, Xiaojuan Jin, Yixin Zhang, Gaofeng Meng, Zhao-Xiang Zhang:
OpenSatMap: A Fine-grained High-resolution Satellite Dataset for Large-scale Map Construction. - Yuanlin Duan, Wensen Mao, He Zhu:
Learning World Models for Unconstrained Goal Navigation. - Celestine Mendler-Dünner, Gabriele Carovano, Moritz Hardt:
An engine not a camera: Measuring performative power of online search. - Gongpei Zhao, Tao Wang, Congyan Lang, Yi Jin, Yidong Li, Haibin Ling:
DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment. - Minghua Liu, Chong Zeng, Xinyue Wei, Ruoxi Shi, Linghao Chen, Chao Xu, Mengqi Zhang, Zhaoning Wang, Xiaoshuai Zhang, Isabella Liu, Hongzhi Wu, Hao Su:
MeshFormer : High-Quality Mesh Generation with 3D-Guided Reconstruction Model. - Huzaifa Pardawala, Siddhant Sukhani, Agam Shah, Veer Kejriwal, Abhishek Pillai, Rohan Bhasin, Andrew DiBiasio, Tarun Mandapati, Dhruv Adha, Sudheer Chava:
SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysis. - Luigi Seminara, Giovanni Maria Farinella, Antonino Furnari:
Differentiable Task Graph Learning: Procedural Activity Representation and Online Mistake Detection from Egocentric Videos. - Haibo Jin, Andy Zhou, Joe D. Menke, Haohan Wang:
Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters. - Victor-Alexandru Padurean, Adish Singla:
Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming. - Hien Vu, Omkar Prabhune, Unmesh Raskar, Dimuth Panditharatne, Hanwook Chung, Christopher Y. Choi, Younghyun Kim:
MmCows: A Multimodal Dataset for Dairy Cattle Monitoring. - Wei Xu, Chunsheng Shi, Sifan Tu, Xin Zhou, Dingkang Liang, Xiang Bai:
A Unified Framework for 3D Scene Understanding. - John L. Zhou, Weizhe Hong, Jonathan C. Kao:
Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents. - Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel:
Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. - Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, Michihiro Yasunaga, Yu Su:
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models. - Chende Zheng, Chenhao Lin, Zhengyu Zhao, Hang Wang, Xu Guo, Shuai Liu, Chao Shen:
Breaking Semantic Artifacts for Generalized AI-generated Image Detection. - Albert Tseng, Qingyao Sun, David Hou, Christopher De Sa:
QTIP: Quantization with Trellises and Incoherence Processing. - Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xiang Li, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj:
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations. - M. Reza Ebrahimi, Jun Chen, Ashish Khisti:
Minimum Entropy Coupling with Bottleneck. - Jonathan Cook, Chris Lu, Edward Hughes, Joel Z. Leibo, Jakob N. Foerster:
Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning. - Ziheng Chen, Yue Song, Rui Wang, Xiaojun Wu, Nicu Sebe:
RMLR: Extending Multinomial Logistic Regression into General Geometries. - Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki:
Wide Two-Layer Networks can Learn from Adversarial Perturbations. - Wenbing Li, Hang Zhou, Junqing Yu, Zikai Song, Wei Yang:
Coupled Mamba: Enhanced Multimodal Fusion with Coupled State Space Model. - Yeming Wen, Swarat Chaudhuri:
Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models. - Jiafei Lyu, Kang Xu, Jiacheng Xu, Mengbei Yan, Jingwen Yang, Zongzhang Zhang, Chenjia Bai, Zongqing Lu, Xiu Li:
ODRL: A Benchmark for Off-Dynamics Reinforcement Learning. - Xinyu Yang, Jixuan Leng, Geyang Guo, Jiawei Zhao, Ryumei Nakada, Linjun Zhang, Huaxiu Yao, Beidi Chen:
S2FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity. - Soufiane Belharbi, Mara KM Whitford, Phuong Hoang, Shakeeb Murtaza, Luke McCaffrey, Eric Granger:
SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image Super-Resolution. - Sayeed Shafayet Chowdhury, Soumyadeep Chandra, Kaushik Roy:
OPEL: Optimal Transport Guided ProcedurE Learning. - Yuzhe Gu, Ziwei Ji, Wenwei Zhang, Chengqi Lyu, Dahua Lin, Kai Chen:
ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models. - Yiting Chen, Jiazi Bu, Junchi Yan:
Unveiling The Matthew Effect Across Channels: Assessing Layer Width Sufficiency via Weight Norm Variance. - Yancheng Liang, Daphne Chen, Abhishek Gupta, Simon S. Du, Natasha Jaques:
Learning to Cooperate with Humans using Generative Agents. - Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Sreenivas Gollapudi, Dee Guo, Ahmed Qureshi:
ReMI: A Dataset for Reasoning with Multiple Images. - Ziyu Xu, Nikos Karampatziakis, Paul Mineiro:
Active, anytime-valid risk controlling prediction sets. - Aditya Vardhan Varre, Margarita Sagitova, Nicolas Flammarion:
SGD vs GD: Rank Deficiency in Linear Networks. - Mingtian Tan, Mike A. Merrill, Vinayak Gupta, Tim Althoff, Tom Hartvigsen:
Are Language Models Actually Useful for Time Series Forecasting? - Zhen Zhang, Xiaohong Chen, Limei Liu, Jie Chen, Junyu Huang, Qilong Feng:
Parameterized Approximation Schemes for Fair-Range Clustering. - Semin Kim, Jaehoon Yoo, Jinwoo Kim, Yeonwoo Cha, Saehoon Kim, Seunghoon Hong:
Simulation-Free Training of Neural ODEs on Paired Data. - Sagi Eppel, Jolina Li, Manuel S. Drehwald, Alán Aspuru-Guzik:
Infusing Synthetic Data with Real-World Patterns for Zero-Shot Material State Segmentation. - Junjie Ni, Guofeng Zhang, Guanglin Li, Yijin Li, Xinyang Liu, Zhaoyang Huang, Hujun Bao:
ETO: Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses. - Yangruibo Ding, Jinjun Peng, Marcus J. Min, Gail E. Kaiser, Junfeng Yang, Baishakhi Ray:
SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning. - Charlie Tan, Inés García-Redondo, Qiquan Wang, Michael M. Bronstein, Anthea Monod:
On the Limitations of Fractal Dimension as a Measure of Generalization. - Yizhuo Ma, Shanmin Pang, Qi Guo, Tianyu Wei, Qing Guo:
ColJailBreak: Collaborative Generation and Editing for Jailbreaking Text-to-Image Deep Generation. - Zhixiong Nan, Xianghong Li, Tao Xiang, Jifeng Dai:
DI-MaskDINO: A Joint Object Detection and Instance Segmentation Model. - Aditya Ramamoorthy, Ruoyu Meng, Vrinda S. Girimaji:
Leveraging partial stragglers within gradient coding. - Steve Hanneke, Vinod Raman, Amirreza Shaeiri, Unique Subedi:
Multiclass Transductive Online Learning. - Nicola Dainese, Matteo Merler, Minttu Alakuijala, Pekka Marttinen:
Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search. - Wenhao Wang, Adam Dziedzic, Michael Backes, Franziska Boenisch:
Localizing Memorization in SSL Vision Encoders. - Xianzhi Zeng, Wenchao Jiang, Shuhao Zhang:
LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication. - Xiaopeng Yu, Jiechuan Jiang, Zongqing Lu:
Opponent Modeling based on Subgoal Inference. - Licong Lin, Jingfeng Wu, Sham M. Kakade, Peter L. Bartlett, Jason D. Lee:
Scaling Laws in Linear Regression: Compute, Parameters, and Data. - Wanyun Cui, Qianle Wang:
Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models. - Hoyeon Chang, Jinho Park, Seonghyeon Ye, Sohee Yang, Youngkyung Seo, Du-Seong Chang, Minjoon Seo:
How Do Large Language Models Acquire Factual Knowledge During Pretraining? - Sandeep Mishra, Oindrila Saha, Alan C. Bovik:
YouDream: Generating Anatomically Controllable Consistent Text-to-3D Animals. - Geelon So, Sanjoy Dasgupta:
Online Consistency of the Nearest Neighbor Rule. - Daniel Prusa, Vojtech Franc:
Constrained Binary Decision Making. - Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang:
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding. - Rhea Sukthanker, Arber Zela, Benedikt Staffler, Aaron Klein, Lennart Purucker, Jörg K. H. Franke, Frank Hutter:
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models. - Yujie Zhao, Jose Aguilar Escamilla, Weyl Lu, Huazheng Wang:
RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning. - Chao Chen, Yu-Shen Liu, Zhizhong Han:
Inferring Neural Signed Distance Functions by Overfitting on Single Noisy Point Clouds through Finetuning Data-Driven based Priors. - Haonan Lin, Wenbin An, Jiahao Wang, Yan Chen, Feng Tian, Mengmeng Wang, Qianying Wang, Guang Dai, Jingdong Wang:
Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery. - George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang:
A Canonicalization Perspective on Invariant and Equivariant Learning. - Zhuofeng Li, Zixing Gou, Xiangnan Zhang, Zhongyuan Liu, Sirui Li, Yuntong Hu, Chen Ling, Zheng Zhang, Liang Zhao:
TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs. - Vladimir Kostic, Grégoire Pacreau, Giacomo Turri, Pietro Novelli, Karim Lounici, Massimiliano Pontil:
Neural Conditional Probability for Uncertainty Quantification. - Juncheng Wu, Zhangkai Ni, Hanli Wang, Wenhan Yang, Yuyin Zhou, Shiqi Wang:
DDR: Exploiting Deep Degradation Response as Flexible Image Descriptor. - Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum S. Anderson, Yaron Singer, Amin Karbasi:
Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. - Albert Q. Jiang, Alicja Ziarko, Bartosz Piotrowski, Wenda Li, Mateja Jamnik, Piotr Milos:
Repurposing Language Models into Embedding Models: Finding the Compute-Optimal Recipe. - Jun Cheng, Shan Tan:
Diffusion Priors for Variational Likelihood Estimation and Image Denoising. - Yuanlin Duan, Guofeng Cui, He Zhu:
Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning. - Ziyi Yang, Xinyu Gao, Yang-Tian Sun, Yihua Huang, Xiaoyang Lyu, Wen Zhou, Shaohui Jiao, Xiaojuan Qi, Xiaogang Jin:
Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting. - Runqian Wang, Soumya Ghosh, David D. Cox, Diego Antognini, Aude Oliva, Rogério Feris, Leonid Karlinsky:
Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. - Yao Ni, Shan Zhang, Piotr Koniusz:
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization. - Yuyang Huo, Lin Lu, Haojie Ren, Changliang Zou:
Real-Time Selection Under General Constraints via Predictive Inference. - Sanghyeob Song, Jaihyun Lew, Hyemi Jang, Sungroh Yoon:
Unsupervised Homography Estimation on Multimodal Image Pair via Alternating Optimization. - Jan-Philipp Fränken, Eric Zelikman, Rafael Rafailov, Kanishk Gandhi, Tobias Gerstenberg, Noah D. Goodman:
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels. - Jack Merullo, Carsten Eickhoff, Ellie Pavlick:
Talking Heads: Understanding Inter-Layer Communication in Transformer Language Models. - Josh Alman, Zhao Song:
The Fine-Grained Complexity of Gradient Computation for Training Large Language Models. - Hongyu Cheng, Amitabh Basu:
Learning Cut Generating Functions for Integer Programming. - Kohei Miyaguchi:
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support. - Jinlong Pang, Jialu Wang, Zhaowei Zhu, Yuanshun Yao, Chen Qian, Yang Liu:
Fairness without Harm: An Influence-Guided Active Sampling Approach. - Yuheng Jing, Bingyun Liu, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng:
Opponent Modeling with In-context Search. - Denis Korzhenkov, Christos Louizos:
On Sampling Strategies for Spectral Model Sharding. - Licheng Zhu, Mathias Oster, Yuehaw Khoo:
S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization. - Yanping Fu, Wenbin Liao, Xinyuan Liu, Hang Xu, Yike Ma, Yucheng Zhang, Feng Dai:
TopoLogic: An Interpretable Pipeline for Lane Topology Reasoning on Driving Scenes. - Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian:
Detecting and Measuring Confounding Using Causal Mechanism Shifts. - Sebastian Ament, Elizabeth Santorella, David Eriksson, Ben Letham, Maximilian Balandat, Eytan Bakshy:
Robust Gaussian Processes via Relevance Pursuit. - Vishaal Udandarao, Ameya Prabhu, Adhiraj Ghosh, Yash Sharma, Philip Torr, Adel Bibi, Samuel Albanie, Matthias Bethge:
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance. - Shinji Ito:
On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice. - Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, Xia Ben Hu:
Gradient Rewiring for Editable Graph Neural Network Training. - Boya Zeng, Yida Yin, Zhuang Liu:
Understanding Bias in Large-Scale Visual Datasets. - Roman Bachmann, Oguzhan Fatih Kar, David Mizrahi, Ali Garjani, Mingfei Gao, David Griffiths, Jiaming Hu, Afshin Dehghan, Amir Zamir:
4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities. - Van Minh Nguyen, Cristian Ocampo-Blandon, Aymen Askri, Louis Leconte, Ba-Hien Tran:
BOLD: Boolean Logic Deep Learning. - Cai Zhou, Xiyuan Wang, Muhan Zhang:
Unifying Generation and Prediction on Graphs with Latent Graph Diffusion. - Diwen Wan, Yuxiang Wang, Ruijie Lu, Gang Zeng:
Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesis. - Aman Patel, Arpita Singhal, Austin Wang, Anusri Pampari, Maya Kasowski, Anshul Kundaje:
DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA. - Felix Fent, Fabian Kuttenreich, Florian Ruch, Farija Rizwin, Stefan Juergens, Lorenz Lechermann, Christian Nissler, Andrea Perl, Ulrich Voll, Min Yan, Markus Lienkamp:
MAN TruckScenes: A multimodal dataset for autonomous trucking in diverse conditions. - Jiaxin Cheng, Zixu Zhao, Tong He, Tianjun Xiao, Zheng Zhang, Yicong Zhou:
Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation. - Yang Yang, Fengqiang Wan, Qing-Yuan Jiang, Yi Xu:
Facilitating Multimodal Classification via Dynamically Learning Modality Gap. - Amit Sinha, Matthieu Geist, Aditya Mahajan:
Periodic agent-state based Q-learning for POMDPs. - Shengnan An, Zexiong Ma, Zeqi Lin, Nanning Zheng, Jian-Guang Lou, Weizhu Chen:
Make Your LLM Fully Utilize the Context. - Bing Li, Cheng Zheng, Wenxuan Zhu, Jinjie Mai, Biao Zhang, Peter Wonka, Bernard Ghanem:
Vivid-ZOO: Multi-View Video Generation with Diffusion Model. - Maxime Zanella, Benoît Gérin, Ismail Ben Ayed:
Boosting Vision-Language Models with Transduction. - Alessandro Betti, Marco Gori:
Nature-Inspired Local Propagation. - Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang:
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs. - Yuefeng Peng, Jaechul Roh, Subhransu Maji, Amir Houmansadr:
OSLO: One-Shot Label-Only Membership Inference Attacks. - Letian Wang, Seung Wook Kim, Jiawei Yang, Cunjun Yu, Boris Ivanovic, Steven L. Waslander, Yue Wang, Sanja Fidler, Marco Pavone, Péter Karkus:
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features. - Lénaïc Chizat, Praneeth Netrapalli:
The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks. - Yulu Gan, Tomer Galanti, Tomaso A. Poggio, Eran Malach:
On the Power of Decision Trees in Auto-Regressive Language Modeling. - Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates:
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation. - Junxiong Wang, Daniele Paliotta, Avner May, Alexander M. Rush, Tri Dao:
The Mamba in the Llama: Distilling and Accelerating Hybrid Models. - Malek Mechergui, Sarath Sreedharan:
Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch. - Walter Gerych, Haoran Zhang, Kimia Hamidieh, Eileen Pan, Maanas K. Sharma, Tom Hartvigsen, Marzyeh Ghassemi:
BendVLM: Test-Time Debiasing of Vision-Language Embeddings. - Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran:
An Analysis of Tokenization: Transformers under Markov Data. - Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Chuyue Sun, Jeff Huang, Cody Hao Yu, Shiyi Cao, Christos Kozyrakis, Ion Stoica, Joseph E. Gonzalez, Clark W. Barrett, Ying Sheng:
SGLang: Efficient Execution of Structured Language Model Programs. - Shuai Li, Zhao Song, Yu Xia, Tong Yu, Tianyi Zhou:
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression. - Usama Muneeb, Mesrob I. Ohannessian:
Induced Model Matching: Restricted Models Help Train Full-Featured Models. - Tzu-Heng Huang, Catherine Cao, Vaishnavi Bhargava, Frederic Sala:
The ALCHEmist: Automated Labeling 500x CHEaper than LLM Data Annotators. - Kang Chen, Shiyan Chen, Jiyuan Zhang, Baoyue Zhang, Yajing Zheng, Tiejun Huang, Zhaofei Yu:
SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams. - Yizhang Zhu, Shiyin Du, Boyan Li, Yuyu Luo, Nan Tang:
Are Large Language Models Good Statisticians? - Junyi Wu, Haoxuan Wang, Yuzhang Shang, Mubarak Shah, Yan Yan:
PTQ4DiT: Post-training Quantization for Diffusion Transformers. - Shreyash Arya, Sukrut Rao, Moritz Böhle, Bernt Schiele:
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable. - Yuxiang Wei, Federico Cassano, Jiawei Liu, Yifeng Ding, Naman Jain, Zachary Mueller, Harm de Vries, Leandro von Werra, Arjun Guha, Lingming Zhang:
SelfCodeAlign: Self-Alignment for Code Generation. - Thorben Werner, Johannes Burchert, Maximilian Stubbemann, Lars Schmidt-Thieme:
A Cross-Domain Benchmark for Active Learning. - Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang, Kun Yuan:
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization. - Cameron Allen, Aaron Kirtland, Ruo Yu Tao, Sam Lobel, Daniel Scott, Nicholas Petrocelli, Omer Gottesman, Ronald Parr, Michael L. Littman, George Konidaris:
Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy. - Anya Sims, Cong Lu, Jakob Foerster, Yee Whye Teh:
The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning. - Mohit Kataria, Sandeep Kumar, Jayadeva:
UGC: Universal Graph Coarsening. - Sangyun Lee, Zinan Lin, Giulia Fanti:
Improving the Training of Rectified Flows. - Zhecan Wang, Junzhang Liu, Chia-Wei Tang, Hani Alomari, Anushka Sivakumar, Rui Sun, Wenhao Li, Md. Atabuzzaman, Hammad A. Ayyubi, Haoxuan You, Alvi Md. Ishmam, Kai-Wei Chang, Shih-Fu Chang, Christopher Thomas:
JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images. - Yinuo Jiang, Xiuchuan Tang, Cheng Cheng, Ye Yuan:
A robust inlier identification algorithm for point cloud registration via 𝓁0-minimization. - Nikiforos Mimikos-Stamatopoulos, Benjamin J. Zhang, Markos A. Katsoulakis:
Score-based generative models are provably robust: an uncertainty quantification perspective. - Ke Sun, Yingnan Zhao, Wulong Liu, Bei Jiang, Linglong Kong:
Distributional Reinforcement Learning with Regularized Wasserstein Loss. - Jiakai Zhang, Qihe Chen, Yan Zeng, Wenyuan Gao, Xuming He, Zhijie Liu, Jingyi Yu:
CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy. - Yang Xu, Yifan Feng, Jun Zhang, Jun-Hai Yong, Yue Gao:
Semi-Open 3D Object Retrieval via Hierarchical Equilibrium on Hypergraph. - Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning. - Jiawei Fan, Chao Li, Xiaolong Liu, Anbang Yao:
ScaleKD: Strong Vision Transformers Could Be Excellent Teachers. - Peter A. Wijeratne, Daniel C. Alexander:
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport. - Dake Bu, Wei Huang, Andi Han, Atsushi Nitanda, Taiji Suzuki, Qingfu Zhang, Hau-San Wong:
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning. - Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Differentially Private Optimization with Sparse Gradients. - Yu-Jie Liang, Zihan Cao, Shangqi Deng, Hong-Xia Dou, Liang-Jian Deng:
Fourier-enhanced Implicit Neural Fusion Network for Multispectral and Hyperspectral Image Fusion. - Jikai Jin, Vasilis Syrgkanis:
Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity. - Qiaoyu Tang, Jiawei Chen, Zhuoqun Li, Bowen Yu, Yaojie Lu, Cheng Fu, Haiyang Yu, Hongyu Lin, Fei Huang, Ben He, Xianpei Han, Le Sun, Yongbin Li:
Self-Retrieval: End-to-End Information Retrieval with One Large Language Model. - Bo Lin, Erick Delage, Timothy C. Y. Chan:
Conformal Inverse Optimization. - Yuqing Yang, Ethan Chern, Xipeng Qiu, Graham Neubig, Pengfei Liu:
Alignment for Honesty. - Jingyuan Zhu, Shiyu Li, Yuxuan Liu, Jian Yuan, Ping Huang, Jiulong Shan, Huimin Ma:
ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models. - Hui-Po Wang, Mario Fritz:
Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models. - Lenart Treven, Bhavya Sukhija, Yarden As, Florian Dörfler, Andreas Krause:
When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL. - Yifei Xia, Fangcheng Fu, Wentao Zhang, Jiawei Jiang, Bin Cui:
Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters. - Hojun Chung, Junseo Lee, Minsoo Kim, Dohyeong Kim, Songhwai Oh:
Adversarial Environment Design via Regret-Guided Diffusion Models. - Zujin Guo, Wei Li, Chen Change Loy:
Generalizable Implicit Motion Modeling for Video Frame Interpolation. - Jin Wu, Haoying Zhou, Peter Kazanzides, Adnan Munawar, Anqi Liu:
SurgicAI: A Hierarchical Platform for Fine-Grained Surgical Policy Learning and Benchmarking. - Yang Cai, Xiangyu Liu, Argyris Oikonomou, Kaiqing Zhang:
Provable Partially Observable Reinforcement Learning with Privileged Information. - Yibo Miao, Yifan Zhu, Lijia Yu, Jun Zhu, Xiao-Shan Gao, Yinpeng Dong:
T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models. - Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel P. Bruinsma, Marlon Tobaben, Antti Honkela, Richard E. Turner:
Noise-Aware Differentially Private Regression via Meta-Learning. - Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atticus Geiger, Dan Jurafsky, Christopher D. Manning, Christopher Potts:
ReFT: Representation Finetuning for Language Models. - Lorenzo Orecchia, Jiawei Hu, Xue He, Wang Mark, Xulei Yang, Min Wu, Xue Geng:
Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming. - Zhihao Yu, Chu Xu, Yujie Jin, Yasha Wang, Junfeng Zhao:
SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction. - Rudolf Laine, Bilal Chughtai, Jan Betley, Kaivalya Hariharan, Mikita Balesni, Jérémy Scheurer, Marius Hobbhahn, Alexander Meinke, Owain Evans:
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs. - Dustin Wright, Christian Igel, Raghavendra Selvan:
BMRS: Bayesian Model Reduction for Structured Pruning. - Han Lu, Xu-Yang Chen, Han-Jia Ye, De-Chuan Zhan:
SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion. - Hongcheng Wang, Peiqi Liu, Wenzhe Cai, Mingdong Wu, Zhengyu Qian, Hao Dong:
MO-DDN: A Coarse-to-Fine Attribute-based Exploration Agent for Multi-Object Demand-driven Navigation. - Roi Livni:
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization. - Yichuan Mo, Yuji Wang, Zeming Wei, Yisen Wang:
Fight Back Against Jailbreaking via Prompt Adversarial Tuning. - Ezra Edelman, Nikolaos Tsilivis, Benjamin L. Edelman, Eran Malach, Surbhi Goel:
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains. - Junxian Wu, Xinyi Ke, Xiaoming Jiang, Huanwen Wu, Youyong Kong, Lizhi Shao:
Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images. - Ian Magnusson, Akshita Bhagia, Valentin Hofmann, Luca Soldaini, Ananya Harsh Jha, Oyvind Tafjord, Dustin Schwenk, Evan Pete Walsh, Yanai Elazar, Kyle Lo, Dirk Groeneveld, Iz Beltagy, Hanna Hajishirzi, Noah A. Smith, Kyle Richardson, Jesse Dodge:
Paloma: A Benchmark for Evaluating Language Model Fit. - Xun Shen, Shuo Jiang, Akifumi Wachi, Kazumune Hashimoto, Sebastien Gros:
Flipping-based Policy for Chance-Constrained Markov Decision Processes. - Kaizhao Liang, Bo Liu, Lizhang Chen, Qiang Liu:
Memory-Efficient LLM Training with Online Subspace Descent. - Cherie Ho, Jiaye Zou, Omar Alama, Sai Mitheran Jagadesh Kumar, Cheng-Yu Chiang, Taneesh Gupta, Chen Wang, Nikhil Varma Keetha, Katia P. Sycara, Sebastian A. Scherer:
Map It Anywhere: Empowering BEV Map Prediction using Large-scale Public Datasets. - Tianxu Li, Kun Zhu, Juan Li, Yang Zhang:
Learning Distinguishable Trajectory Representation with Contrastive Loss. - Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik:
HEALNet: Multimodal Fusion for Heterogeneous Biomedical Data. - Yuxiao Wen, Yanjun Han, Zhengyuan Zhou:
Stochastic contextual bandits with graph feedback: from independence number to MAS number. - Nadav Merlis:
Reinforcement Learning with Lookahead Information. - Chuanhao Li, Zhen Li, Chenchen Jing, Shuo Liu, Wenqi Shao, Yuwei Wu, Ping Luo, Yu Qiao, Kaipeng Zhang:
SearchLVLMs: A Plug-and-Play Framework for Augmenting Large Vision-Language Models by Searching Up-to-Date Internet Knowledge. - Zhechao Wang, Peirui Cheng, Minxing Chen, Pengju Tian, Zhirui Wang, Xinming Li, Xue Yang, Xian Sun:
Drones Help Drones: A Collaborative Framework for Multi-Drone Object Trajectory Prediction and Beyond. - Kun Wang, Zhiqiang Yan, Junkai Fan, Wanlu Zhu, Xiang Li, Jun Li, Jian Yang:
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine Domain. - Jung-hun Kim, Min-hwan Oh:
Queueing Matching Bandits with Preference Feedback. - Akshatha Arodi, Margaux Luck, Jean-Luc Bedwani, Aldo Zaimi, Ge Li, Nicolas Pouliot, Julien Beaudry, Gaétan Marceau-Caron:
CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset. - Ali Hassani, Wen-Mei Hwu, Humphrey Shi:
Faster Neighborhood Attention: Reducing the O(n^2) Cost of Self Attention at the Threadblock Level. - Dan Zhang, Sining Zhoubian, Ziniu Hu, Yisong Yue, Yuxiao Dong, Jie Tang:
ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search. - Yitong Dong, Yijin Li, Zhaoyang Huang, Weikang Bian, Jingbo Liu, Hujun Bao, Zhaopeng Cui, Hongsheng Li, Guofeng Zhang:
A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding. - Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee, Peter J. Stuckey:
Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs. - Nikos Tsikouras, Constantine Caramanis, Christos Tzamos:
Optimization Can Learn Johnson Lindenstrauss Embeddings. - Ziqi Yang, Zhaopeng Peng, Zihui Wang, Jianzhong Qi, Chaochao Chen, Weike Pan, Chenglu Wen, Cheng Wang, Xiaoliang Fan:
Federated Graph Learning for Cross-Domain Recommendation. - Xiao Zhang, Miao Li, Ji Wu:
Co-occurrence is not Factual Association in Language Models. - Pengkun Wang, Zhe Zhao, Haibin Wen, Fanfu Wang, Binwu Wang, Qingfu Zhang, Yang Wang:
LLM-AutoDA: Large Language Model-Driven Automatic Data Augmentation for Long-tailed Problems. - Rohan R. Paleja, Michael Munje, Kimberlee Chestnut Chang, Reed Jensen, Matthew C. Gombolay:
Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems. - Seonghyun Ban, Heesan Kong, Kee-Eung Kim:
Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning. - Wei Wu, Kecheng Zheng, Shuailei Ma, Fan Lu, Yuxin Guo, Yifei Zhang, Wei Chen, Qingpei Guo, Yujun Shen, Zheng-Jun Zha:
LoTLIP: Improving Language-Image Pre-training for Long Text Understanding. - Ge Yan, Mengfei Ran, Ruocheng Wang, Kaisen Pan, Junchi Yan:
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz. - Vijaya Raghavan T. Ramkumar, Elahe Arani, Bahram Zonooz:
Dynamic Neural Regeneration: Enhancing Deep Learning Generalization on Small Datasets. - Chia-Yi Hsu, Yu-Lin Tsai, Chih-Hsun Lin, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang:
Safe LoRA: The Silver Lining of Reducing Safety Risks when Finetuning Large Language Models. - Konstantinos Kogkalidis, Orestis Melkonian, Jean-Philippe Bernardy:
Learning Structure-Aware Representations of Dependent Types. - Anil Kag, Huseyin Coskun, Jierun Chen, Junli Cao, Willi Menapace, Aliaksandr Siarohin, Sergey Tulyakov, Jian Ren:
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation. - Yanbang Wang, Hejie Cui, Jon M. Kleinberg:
Microstructures and Accuracy of Graph Recall by Large Language Models. - Cheng Li, Damien Teney, Linyi Yang, Qingsong Wen, Xing Xie, Jindong Wang:
CulturePark: Boosting Cross-cultural Understanding in Large Language Models. - Weichao Yang, Hongwei Shi, Xu Guo, Changliang Zou:
Robust group and simultaneous inferences for high-dimensional single index model. - Ye He, Alireza Mousavi Hosseini, Krishnakumar Balasubramanian, Murat A. Erdogdu:
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers. - Jianke Yang, Wang Rao, Nima Dehmamy, Robin Walters, Rose Yu:
Symmetry-Informed Governing Equation Discovery. - Bo Li, Wei Wang, Peng Ye:
The Limits of Differential Privacy in Online Learning. - Francesco Paissan, Luca Della Libera, Mirco Ravanelli, Cem Subakan:
Listenable Maps for Zero-Shot Audio Classifiers. - Teodora Popordanoska, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko:
LaSCal: Label-Shift Calibration without target labels. - Simone Parisi, Alireza Kazemipour, Michael Bowling:
Beyond Optimism: Exploration With Partially Observable Rewards. - Jiaming Lv, Haoyuan Yang, Peihua Li:
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation. - Vahid Balazadeh Meresht, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan, Vasilis Syrgkanis:
Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity. - Hanwen Jiang, Haitao Yang, Georgios Pavlakos, Qixing Huang:
CoFie: Learning Compact Neural Surface Representations with Coordinate Fields. - Huancheng Chen, Haris Vikalo:
Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning. - Yao Tang, Zhihui Xie, Zichuan Lin, Deheng Ye, Shuai Li:
Learning Versatile Skills with Curriculum Masking. - Hongren Yan, Yuhua Qian, Furong Peng, Jiachen Luo, Zheqing Zhu, Feijiang Li:
Neural Collapse To Multiple Centers For Imbalanced Data. - Wenhao Wang, Yi Yang:
VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models. - Junyi Cao, Shanyan Guan, Yanhao Ge, Wei Li, Xiaokang Yang, Chao Ma:
NeuMA: Neural Material Adaptor for Visual Grounding of Intrinsic Dynamics. - Jiajun Wang, Morteza Ghahremani, Yitong Li, Björn Ommer, Christian Wachinger:
Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation. - Diyang Li:
Generalized Fast Exact Conformalization. - Wei Ji, Jingjing Li, Wenbo Li, Yilin Shen, Li Cheng, Hongxia Jin:
Unleashing Multispectral Video's Potential in Semantic Segmentation: A Semi-supervised Viewpoint and New UAV-View Benchmark. - Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang:
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. - Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Kevin Li, Elliot Catt, John Reid, Cannada Lewis, Joel Veness, Tim Genewein:
Amortized Planning with Large-Scale Transformers: A Case Study on Chess. - Yuanqi Du, Michael Plainer, Rob Brekelmans, Chenru Duan, Frank Noé, Carla P. Gomes, Alán Aspuru-Guzik, Kirill Neklyudov:
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling. - Jiong Zhu, Gaotang Li, Yao-An Yang, Jing Zhu, Xuehao Cui, Danai Koutra:
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks. - Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam:
Breaking the curse of dimensionality in structured density estimation. - Geng Chen, Yinxu Jia, Guanghui Wang, Changliang Zou:
Zipper: Addressing Degeneracy in Algorithm-Agnostic Inference. - Arushi Jain, Josiah Hanna, Doina Precup:
Adaptive Exploration for Data-Efficient General Value Function Evaluations. - Haoyu Geng, Hang Ruan, Runzhong Wang, Yang Li, Yang Wang, Lei Chen, Junchi Yan:
Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime. - Saravanan Kandasamy, Dheeraj Nagaraj:
The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models. - Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang:
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models. - Jon M. Kleinberg, Sendhil Mullainathan:
Language Generation in the Limit. - Lifeng Qiao, Peng Ye, Yuchen Ren, Weiqiang Bai, Chaoqi Liang, Xinzhu Ma, Nanqing Dong, Wanli Ouyang:
Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA. - Tian Xu, Zhilong Zhang, Ruishuo Chen, Yihao Sun, Yang Yu:
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation. - Qin Zhang, Zelin Shi, Shirui Pan, Junyang Chen, Huisi Wu, Xiaojun Chen:
EGonc : Energy-based Open-Set Node Classification with substitute Unknowns. - Marco Fumero, Marco Pegoraro, Valentino Maiorca, Francesco Locatello, Emanuele Rodolà:
Latent Functional Maps: a spectral framework for representation alignment. - Sean Jaffe, Alexander Davydov, Deniz Lapsekili, Ambuj K. Singh, Francesco Bullo:
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees. - Mincheol Chang, Siyeong Lee, Jinkyu Kim, Namil Kim:
Just Add $100 More: Augmenting Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem. - Jer Pelhan, Alan Lukezic, Vitjan Zavrtanik, Matej Kristan:
A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation. - Anirudh Sundar, Jin Xu, William Gay, Christopher Richardson, Larry Heck:
cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers. - Shuhao Chen, Weisen Jiang, Baijiong Lin, James T. Kwok, Yu Zhang:
RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models. - Wei Chen, Xixuan Hao, Yuankai Wu, Yuxuan Liang:
Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth. - Yuzhuang Xu, Xu Han, Zonghan Yang, Shuo Wang, Qingfu Zhu, Zhiyuan Liu, Weidong Liu, Wanxiang Che:
OneBit: Towards Extremely Low-bit Large Language Models. - Xuezhi Wang, Denny Zhou:
Chain-of-Thought Reasoning Without Prompting. - Tam Nguyen, Anh-Dzung Doan, Zhipeng Cai, Tat-Jun Chin:
Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover. - Liping Yi, Han Yu, Chao Ren, Gang Wang, Xiaoguang Liu, Xiaoxiao Li:
Federated Model Heterogeneous Matryoshka Representation Learning. - Haotian Qian, Yinda Chen, Shengtao Lou, Fahad Shahbaz Khan, Xiaogang Jin, Deng-Ping Fan:
MaskFactory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentation. - Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang:
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers. - Agniv Bandyopadhyay, Sandeep Juneja, Shubhada Agrawal:
Optimal Top-Two Method for Best Arm Identification and Fluid Analysis. - Juhan Bae, Wu Lin, Jonathan Lorraine, Roger B. Grosse:
Training Data Attribution via Approximate Unrolling. - Jinliang Deng, Feiyang Ye, Du Yin, Xuan Song, Ivor W. Tsang, Hui Xiong:
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting. - Michael Munn, Benoit Dherin, Javier Gonzalvo:
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning. - Susung Hong:
Smoothed Energy Guidance: Guiding Diffusion Models with Reduced Energy Curvature of Attention. - Yunfeng Fan, Wenchao Xu, Haozhao Wang, Song Guo:
Cross-modal Representation Flattening for Multi-modal Domain Generalization. - Wanyi Ning, Jingyu Wang, Qi Qi, Mengde Zhu, Haifeng Sun, Daixuan Cheng, Jianxin Liao, Ce Zhang:
FM-Delta: Lossless Compression for Storing Massive Fine-tuned Foundation Models. - Quentin Delfosse, Sebastian Sztwiertnia, Mark Rothermel, Wolfgang Stammer, Kristian Kersting:
Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents. - Ábel Ságodi, Guillermo Martín-Sánchez, Piotr A. Sokól, Memming Park:
Back to the Continuous Attractor. - Tian Lan, Wenwei Zhang, Chen Xu, Heyan Huang, Dahua Lin, Kai Chen, Xian-Ling Mao:
CriticEval: Evaluating Large-scale Language Model as Critic. - Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Ullrich Köthe:
Learning Distributions on Manifolds with Free-Form Flows. - Liyang Zhu, Amina Manseur, Meng Ding, Jinyan Liu, Jinhui Xu, Di Wang:
Truthful High Dimensional Sparse Linear Regression. - Minjong Yoo, Jinwoo Jang, Wei-Jin Park, Honguk Woo:
Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Following. - Jingchang Chen, Hongxuan Tang, Zheng Chu, Qianglong Chen, Zekun Wang, Ming Liu, Bing Qin:
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation. - Lukas Klein, Carsten T. Lüth, Udo Schlegel, Till J. Bungert, Mennatallah El-Assady, Paul F. Jaeger:
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics. - Seong Hyeon Park, Huiwon Jang, Byungwoo Jeon, Sukmin Yun, Paul Hongsuck Seo, Jinwoo Shin:
TrackIME: Enhanced Video Point Tracking via Instance Motion Estimation. - Yicheng Luo, Zhen Liu, Linghao Wang, Binquan Wu, Junhao Zheng, Qianli Ma:
Knowledge-Empowered Dynamic Graph Network for Irregularly Sampled Medical Time Series. - Yulong Hui, Yao Lu, Huanchen Zhang:
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-World Document Analysis. - Yao Shu, Jiongfeng Fang, Ying He, Fei Richard Yu:
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations. - David Schneider, Simon Reiß, Marco Kugler, Alexander Jaus, Kunyu Peng, Susanne Sutschet, M. Saquib Sarfraz, Sven Matthiesen, Rainer Stiefelhagen:
Muscles in Time: Learning to Understand Human Motion In-Depth by Simulating Muscle Activations. - Hao Xu, Jia Pan:
HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems. - Frederic Z. Zhang, Paul Albert, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad:
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling. - Jiacheng Zhang, Jie Wu, Yuxi Ren, Xin Xia, Huafeng Kuang, Pan Xie, Jiashi Li, Xuefeng Xiao, Weilin Huang, Shilei Wen, Lean Fu, Guanbin Li:
UniFL: Improve Latent Diffusion Model via Unified Feedback Learning. - Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas, Jelena Diakonikolas:
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise. - Sangwoo Hwang, Seunghyun Lee, Dahoon Park, Donghun Lee, Jaeha Kung:
SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation. - Lianyu Hu, Tongkai Shi, Wei Feng, Fanhua Shang, Liang Wan:
Deep Correlated Prompting for Visual Recognition with Missing Modalities. - William Qian, Jacob A. Zavatone-Veth, Benjamin S. Ruben, Cengiz Pehlevan:
Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics. - Yihe Deng, Chenchen Ye, Zijie Huang, Mingyu Derek Ma, Yiwen Kou, Wei Wang:
GraphVis: Boosting LLMs with Visual Knowledge Graph Integration. - Hanqing Zhu, Wenyan Cong, Guojin Chen, Shupeng Ning, Ray T. Chen, Jiaqi Gu, David Z. Pan:
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices. - Krishna Prasad Neupane, Ervine Zheng, Qi Yu:
Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation. - Yian Wang, Xiaowen Qiu, Jiageng Liu, Zhehuan Chen, Jiting Cai, Yufei Wang, Tsun-Hsuan Johnson Wang, Zhou Xian, Chuang Gan:
Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting. - Tyler Ingebrand, Adam J. Thorpe, Ufuk Topcu:
Zero-Shot Transfer of Neural ODEs. - Julien Pourcel, Cédric Colas, Gaia Molinaro, Pierre-Yves Oudeyer, Laetitia Teodorescu:
ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models. - David Yunis, Justin Jung, Falcon Z. Dai, Matthew R. Walter:
Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning. - Hangcheng Liu, Zhenhu Wu, Hao Wang, Xingshuo Han, Shangwei Guo, Tao Xiang, Tianwei Zhang:
Beware of Road Markings: A New Adversarial Patch Attack to Monocular Depth Estimation. - Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam:
Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers. - Yibin Wang, Haizhou Shi, Ligong Han, Dimitris N. Metaxas, Hao Wang:
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models. - Taolin Zhang, Jinpeng Wang, Hang Guo, Tao Dai, Bin Chen, Shu-Tao Xia:
BoostAdapter: Improving Vision-Language Test-Time Adaptation via Regional Bootstrapping. - Ziquan Wei, Tingting Dan, Jiaqi Ding, Guorong Wu:
NeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes. - Xing Han, Huy Nguyen, Carl Harris, Nhat Ho, Suchi Saria:
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion. - Yi Zhu, Surya Koppisetti, Trang Tran, Gaurav Bharaj:
SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection. - Siddharth Nayak, Adelmo Morrison Orozco, Marina Ten Have, Jackson Zhang, Vittal Thirumalai, Darren Chen, Aditya Kapoor, Eric Robinson, Karthik Gopalakrishnan, James Harrison, Anuj Mahajan, Brian Ichter, Hamsa Balakrishnan:
Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments. - Radu Marinescu, Junkyu Lee, Debarun Bhattacharjya, Fábio G. Cozman, Alexander G. Gray:
Abductive Reasoning in Logical Credal Networks. - Sangeek Hyun, Jae-Pil Heo:
GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats. - Stephen Boyd, Tetiana Parshakova, Ernest K. Ryu, Jaewook J. Suh:
Optimization Algorithm Design via Electric Circuits. - Jialong Wu, Shaofeng Yin, Ningya Feng, Xu He, Dong Li, Jianye Hao, Mingsheng Long:
iVideoGPT: Interactive VideoGPTs are Scalable World Models. - Vinod Raman, Unique Subedi, Ambuj Tewari:
Smoothed Online Classification can be Harder than Batch Classification. - Edwige Cyffers, Muni Sreenivas Pydi, Jamal Atif, Olivier Cappé:
Optimal Classification under Performative Distribution Shift. - Ashwin Sankar, Srija Anand, Praveen Srinivasa Varadhan, Sherry Thomas, Mehak Singal, Shridhar Kumar, Deovrat Mehendale, Aditi Krishana, Giri Raju, Mitesh M. Khapra:
IndicVoices-R: Unlocking a Massive Multilingual Multi-speaker Speech Corpus for Scaling Indian TTS. - Yibo Miao, Yinpeng Dong, Jinlai Zhang, Lijia Yu, Xiao Yang, Xiao-Shan Gao:
Improving Robustness of 3D Point Cloud Recognition from a Fourier Perspective. - Jingbo Zhou, Yixuan Du, Ruqiong Zhang, Jun Xia, Zhizhi Yu, Zelin Zang, Di Jin, Carl Yang, Rui Zhang, Stan Z. Li:
Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module. - David P. Woodruff, Taisuke Yasuda:
John Ellipsoids via Lazy Updates. - Jaewon Chu, Jinyoung Park, Seunghun Lee, Hyunwoo J. Kim:
Inversion-based Latent Bayesian Optimization. - Yefei He, Luoming Zhang, Weijia Wu, Jing Liu, Hong Zhou, Bohan Zhuang:
ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification. - Parand A. Alamdari, Soroush Ebadian, Ariel D. Procaccia:
Policy Aggregation. - Maxime Darrin, Philippe Formont, Ismail Ben Ayed, Jackie CK Cheung, Pablo Piantanida:
When is an Embedding Model More Promising than Another? - Washim Uddin Mondal, Vaneet Aggarwal:
Sample-Efficient Constrained Reinforcement Learning with General Parameterization. - Yilun Zheng, Sitao Luan, Lihui Chen:
What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks. - Yuanhao Cai, Zihao Xiao, Yixun Liang, Minghan Qin, Yulun Zhang, Xiaokang Yang, Yaoyao Liu, Alan L. Yuille:
HDR-GS: Efficient High Dynamic Range Novel View Synthesis at 1000x Speed via Gaussian Splatting. - Zhao Zhang, Ziwei Zhao, Dong Wang, Liwei Wang:
GraphMorph: Tubular Structure Extraction by Morphing Predicted Graphs. - Youssef Allouah, Akash Dhasade, Rachid Guerraoui, Nirupam Gupta, Anne-Marie Kermarrec, Rafael Pinot, Rafael Pires, Rishi Sharma:
Revisiting Ensembling in One-Shot Federated Learning. - Ruofeng Yang, Bo Jiang, Cheng Chen, Ruinan Jin, Baoxiang Wang, Shuai Li:
Few-Shot Diffusion Models Escape the Curse of Dimensionality. - Richard Ren, Steven Basart, Adam Khoja, Alice Gatti, Long Phan, Xuwang Yin, Mantas Mazeika, Alexander Pan, Gabriel Mukobi, Ryan H. Kim, Stephen Fitz, Dan Hendrycks:
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? - Liang Han, Junsheng Zhou, Yu-Shen Liu, Zhizhong Han:
Binocular-Guided 3D Gaussian Splatting with View Consistency for Sparse View Synthesis. - Chenhao Zhou, Zebang Shen, Zhang Chao, Hanbin Zhao, Hui Qian:
Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding. - Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, Tri Dao:
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision. - Xin Yuan, Michael Maire:
Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation. - Mikhail Gorbunov, Nikolay Yudin, Vera Soboleva, Aibek Alanov, Alexey Naumov, Maxim Rakhuba:
Group and Shuffle: Efficient Structured Orthogonal Parametrization. - Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Romit Maulik, Rao Kotamarthi, Ian T. Foster, Sandeep Madireddy, Aditya Grover:
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. - Arjun Panickssery, Samuel R. Bowman, Shi Feng:
LLM Evaluators Recognize and Favor Their Own Generations. - Chenyang Ma, Kai Lu, Ta Ying Cheng, Niki Trigoni, Andrew Markham:
SpatialPIN: Enhancing Spatial Reasoning Capabilities of Vision-Language Models through Prompting and Interacting 3D Priors. - Xiusheng Huang, Jiaxiang Liu, Yequan Wang, Kang Liu:
Reasons and Solutions for the Decline in Model Performance after Editing. - Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman:
Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization. - Qi Wang, Pu Ren, Hao Zhou, Xin-Yang Liu, Zhiwen Deng, Yi Zhang, Zeruizhi Cheng, Hongsheng Liu, Zidong Wang, Jian-Xun Wang, Ji-Rong Wen, Hao Sun, Yang Liu:
P2C2Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics. - Haotian Jiang, Qianxiao Li:
Approximation Rate of the Transformer Architecture for Sequence Modeling. - Jiyuan Tan, Jose H. Blanchet, Vasilis Syrgkanis:
Consistency of Neural Causal Partial Identification. - Ting Guo, Da Wang, Jiye Liang, Kaihan Zhang, Jianchao Zeng:
SpeAr: A Spectral Approach for Zero-Shot Node Classification. - Bowen Cao, Deng Cai, Zhisong Zhang, Yuexian Zou, Wai Lam:
On the Worst Prompt Performance of Large Language Models. - Hadi Hosseini, Sanjukta Roy, Duohan Zhang:
Putting Gale & Shapley to Work: Guaranteeing Stability Through Learning. - Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan:
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models. - Yiling Chen, Tao Lin, Ariel D. Procaccia, Aaditya Ramdas, Itai Shapira:
Bias Detection via Signaling. - Ryan Greenblatt, Fabien Roger, Dmitrii Krasheninnikov, David Krueger:
Stress-Testing Capability Elicitation With Password-Locked Models. - Zhengxiang Shi, Adam X. Yang, Bin Wu, Laurence Aitchison, Emine Yilmaz, Aldo Lipani:
Instruction Tuning With Loss Over Instructions. - Marco Bornstein, Amrit Singh Bedi, Abdirisak Mohamed, Furong Huang:
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? - Yuzhou Gu, Nikki Lijing Kuang, Yian Ma, Zhao Song, Lichen Zhang:
Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk. - Tianlong Xu, Chen Wang, Gaoyang Liu, Yang Yang, Kai Peng, Wei Liu:
United We Stand, Divided We Fall: Fingerprinting Deep Neural Networks via Adversarial Trajectories. - Kevin Qinghong Lin, Linjie Li, Difei Gao, Qinchen Wu, Mingyi Yan, Zhengyuan Yang, Lijuan Wang, Mike Zheng Shou:
VideoGUI: A Benchmark for GUI Automation from Instructional Videos. - Hanyang Yuan, Jiarong Xu, Renhong Huang, Mingli Song, Chunping Wang, Yang Yang:
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach. - Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang, Le Song:
Training Compute-Optimal Protein Language Models. - Jaegyun Park, Dae-Won Kim, Jaesung Lee:
CALANet: Cheap All-Layer Aggregation for Human Activity Recognition. - Yu-Liang Zhan, Zhong-Yi Lu, Hao Sun, Ze-Feng Gao:
Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation. - Oliver Richardson, Spencer J. Peters, Joseph Y. Halpern:
Qualitative Mechanism Independence. - Daniel Miao, Gilad Lerman, Joe Kileel:
Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor. - Pha A. Nguyen, Ngan Le, Jackson David Cothren, Alper Yilmaz, Khoa Luu:
DINTR: Tracking via Diffusion-based Interpolation. - Fangyun Wei, Jinjing Zhao, Kun Yan, Hongyang Zhang, Chang Xu:
A Large-Scale Human-Centric Benchmark for Referring Expression Comprehension in the LMM Era. - Zhiwei Lin, Yongtao Wang, Zhi Tang:
Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts. - Tao Jiang, Lei Yuan, Lihe Li, Cong Guan, Zongzhang Zhang, Yang Yu:
Multi-Agent Domain Calibration with a Handful of Offline Data. - Jae-Yong Baek, Yong-Sang Yoo, Seung Hwan Bae:
A New Multi-Source Light Detection Benchmark and Semi-Supervised Focal Light Detection. - Skander Moalla, Andrea Miele, Daniil Pyatko, Razvan Pascanu, Caglar Gulcehre:
No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO. - Xin Shen, Heming Du, Hongwei Sheng, Shuyun Wang, Hui Chen, Huiqiang Chen, Zhuojie Wu, Xiaobiao Du, Jiaying Ying, Ruihan Lu, Qingzheng Xu, Xin Yu:
MM-WLAuslan: Multi-View Multi-Modal Word-Level Australian Sign Language Recognition Dataset. - Qingyang Zhang, Qiuxuan Feng, Joey Tianyi Zhou, Yatao Bian, Qinghua Hu, Changqing Zhang:
The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection. - Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H. Markosyan, Manish Bhatt, Yuning Mao, Minqi Jiang, Jack Parker-Holder, Jakob Foerster, Tim Rocktäschel, Roberta Raileanu:
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. - Sofia Ek, Dave Zachariah:
Externally Valid Policy Evaluation from Randomized Trials Using Additional Observational Data. - Junyu Chen, Binh T. Nguyen, Shang Koh, Yong Sheng Soh:
Semidefinite Relaxations of the Gromov-Wasserstein Distance. - Bowen Li, Zhaoyu Li, Qiwei Du, Jinqi Luo, Wenshan Wang, Yaqi Xie, Simon Stepputtis, Chen Wang, Katia P. Sycara, Pradeep Ravikumar, Alexander G. Gray, Xujie Si, Sebastian A. Scherer:
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation. - Andrew Bond, Zafer Dogan:
Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning. - Thomas Fel, Louis Béthune, Andrew K. Lampinen, Thomas Serre, Katherine L. Hermann:
Understanding Visual Feature Reliance through the Lens of Complexity. - Jiannan Wu, Muyan Zhong, Sen Xing, Zeqiang Lai, Zhaoyang Liu, Zhe Chen, Wenhai Wang, Xizhou Zhu, Lewei Lu, Tong Lu, Ping Luo, Yu Qiao, Jifeng Dai:
VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks. - Xueying Bai, Jinghuan Shang, Yifan Sun, Niranjan Balasubramanian:
Continual Learning with Global Alignment. - Jiaqi Li, Yiran Wang, Jinghong Zheng, Zihao Huang, Ke Xian, Zhiguo Cao, Jianming Zhang:
Self-Distilled Depth Refinement with Noisy Poisson Fusion. - Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Scalable DP-SGD: Shuffling vs. Poisson Subsampling. - Kuo Yang, Zhengyang Zhou, Qihe Huang, Limin Li, Yuxuan Liang, Yang Wang:
Improving Generalization of Dynamic Graph Learning via Environment Prompt. - Prasenjit Karmakar, Swadhin Pradhan, Sandip Chakraborty:
Indoor Air Quality Dataset with Activities of Daily Living in Low to Middle-income Communities. - Penghui Ruan, Pichao Wang, Divya Saxena, Jiannong Cao, Yuhui Shi:
Enhancing Motion in Text-to-Video Generation with Decomposed Encoding and Conditioning. - Bhavin Jawade, Alexander Stone, Deen Dayal Mohan, Xiao Wang, Srirangaraj Setlur, Venu Govindaraju:
ProxyFusion: Face Feature Aggregation Through Sparse Experts. - Hao Tang, Darren Key, Kevin Ellis:
WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment. - Tianqi Tang, Shohreh Deldari, Hao Xue, Celso de Melo, Flora D. Salim:
ViLCo-Bench: VIdeo Language COntinual learning Benchmark. - Renlang Huang, Yufan Tang, Jiming Chen, Liang Li:
A Consistency-Aware Spot-Guided Transformer for Versatile and Hierarchical Point Cloud Registration. - Guy Ohayon, Michael Elad, Tomer Michaeli:
Perceptual Fairness in Image Restoration. - Abdullah Akgül, Manuel Haussmann, Melih Kandemir:
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning. - Jake A. Soloff, Rina Barber, Rebecca Willett:
Building a stable classifier with the inflated argmax. - Marvin Alles, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl:
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning. - Kanghao Chen, Hangyu Li, Jiazhou Zhou, Zeyu Wang, Lin Wang:
LaSe-E2V: Towards Language-guided Semantic-aware Event-to-Video Reconstruction. - Yunan Lu, Xiuyi Jia:
Predicting Label Distribution from Ternary Labels. - Yiwei Zhang, Jin Gao, Fudong Ge, Guan Luo, Bing Li, Zhao-Xiang Zhang, Haibin Ling, Weiming Hu:
VQ-Map: Bird's-Eye-View Map Layout Estimation in Tokenized Discrete Space via Vector Quantization. - Runhua Xu, Shiqi Gao, Chao Li, James Joshi, Jianxin Li:
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning. - Tian Qiu, Chenchao Gao, Zunlei Feng, Jie Lei, Bingde Hu, Xingen Wang, Yi Gao, Mingli Song:
Dual-Perspective Activation: Efficient Channel Denoising via Joint Forward-Backward Criterion for Artificial Neural Networks. - Junyi Li, Heng Huang:
Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling. - Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup:
Offline Multitask Representation Learning for Reinforcement Learning. - Songfu Cai, Fei Han, Xuanyu Cao:
Performative Control for Linear Dynamical Systems. - Armand Kassaï Koupaï, Jorge Mifsut Benet, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari:
Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning. - Jerry Yao-Chieh Hu, Dennis Wu, Han Liu:
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes. - Mathieu Even, Luca Ganassali, Jakob Maier, Laurent Massoulié:
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem. - Qiang Liu, Shaozhen Liu, Xin Sun, Shu Wu, Liang Wang:
Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction. - Silviu Pitis, Ziang Xiao, Nicolas Le Roux, Alessandro Sordoni:
Improving Context-Aware Preference Modeling for Language Models. - Shuai Liu, Alex Ayoub, Flore Sentenac, Xiaoqi Tan, Csaba Szepesvári:
Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits. - Karl Chahine, Hyeji Kim:
Neural Cover Selection for Image Steganography. - Chia-Hsiang Kao, Bharath Hariharan:
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning. - Hao Wu, Hanwen Zhang:
Faster Differentially Private Top-k Selection: A Joint Exponential Mechanism with Pruning. - Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang:
A Tractable Inference Perspective of Offline RL. - Daksh Mittal, Yuanzhe Ma, Shalmali Joshi, Hongseok Namkoong:
Adaptive Labeling for Efficient Out-of-distribution Model Evaluation. - Hongyao Tang, Min Zhang, Chen Chen, Jianye Hao:
The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space. - Yuhong Chou, Man Yao, Kexin Wang, Yuqi Pan, Rui-Jie Zhu, Jibin Wu, Yiran Zhong, Yu Qiao, Bo Xu, Guoqi Li:
MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map. - Kai Liu, Haotong Qin, Yong Guo, Xin Yuan, Linghe Kong, Guihai Chen, Yulun Zhang:
2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution. - Lei Shi, Waverly Wei, Jingshen Wang:
Using Surrogates in Covariate-adjusted Response-adaptive Randomization Experiments with Delayed Outcomes. - Ye He, Kevin Rojas, Molei Tao:
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion. - Haoyang He, Yuhu Bai, Jiangning Zhang, Qingdong He, Hongxu Chen, Zhenye Gan, Chengjie Wang, Xiangtai Li, Guanzhong Tian, Lei Xie:
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection. - Xuefei Ning, Zifu Wang, Shiyao Li, Zinan Lin, Peiran Yao, Tianyu Fu, Matthew B. Blaschko, Guohao Dai, Huazhong Yang, Yu Wang:
Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study. - Oscar Leong, Eliza O'Reilly, Yong Sheng Soh:
The Star Geometry of Critic-Based Regularizer Learning. - Hamed Shirzad, Honghao Lin, Balaji Venkatachalam, Ameya Velingker, David P. Woodruff, Danica J. Sutherland:
Even Sparser Graph Transformers. - Yuhang Cai, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett:
Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization. - Yaqi Duan, Martin J. Wainwright:
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces. - Kaito Ito, Kenji Kashima:
Risk-sensitive control as inference with Rényi divergence. - Zian Qian, Chenyang Qi, Ka Lung Law, Hao Fu, Chenyang Lei, Qifeng Chen:
Adaptive Domain Learning for Cross-domain Image Denoising. - Nikunj Saunshi, Stefani Karp, Shankar Krishnan, Sobhan Miryoosefi, Sashank Jakkam Reddi, Sanjiv Kumar:
On the Inductive Bias of Stacking Towards Improving Reasoning. - Xu Zhang, Peiyao Guo, Ming Lu, Zhan Ma:
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation. - Shubhankar Borse, Shreya Kadambi, Nilesh Prasad Pandey, Kartikeya Bhardwaj, Viswanath Ganapathy, Sweta Priyadarshi, Risheek Garrepalli, Rafael Esteves, Munawar Hayat, Fatih Porikli:
FouRA: Fourier Low-Rank Adaptation. - Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca D. Dragan:
Learning to Assist Humans without Inferring Rewards. - Zihan Luo, Hong Huang, Yongkang Zhou, Jiping Zhang, Nuo Chen, Hai Jin:
Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections. - Ching-An Cheng, Allen Nie, Adith Swaminathan:
Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs. - Arvind Vepa, Zukang Yang, Andrew Choi, Jungseock Joo, Fabien Scalzo, Yizhou Sun:
Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation. - Yipei Wang, Jeffrey Siskind, Xiaoqian Wang:
Great Minds Think Alike: The Universal Convergence Trend of Input Salience. - Dingling Yao, Caroline Muller, Francesco Locatello:
Marrying Causal Representation Learning with Dynamical Systems for Science. - Tao Zhang, Xiangtai Li, Hao Fei, Haobo Yuan, Shengqiong Wu, Shunping Ji, Chen Change Loy, Shuicheng Yan:
OMG-LLaVA: Bridging Image-level, Object-level, Pixel-level Reasoning and Understanding. - Yibo Yang, Xiaojie Li, Zhongzhu Zhou, Shuaiwen Song, Jianlong Wu, Liqiang Nie, Bernard Ghanem:
CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuning. - Wolfgang Stammer, Antonia Wüst, David Steinmann, Kristian Kersting:
Neural Concept Binder. - Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong, Beidi Chen, Lili Yu, Hao Zhang, Jonathan May, Luke Zettlemoyer, Omer Levy, Chunting Zhou:
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length. - Jannik Franzen, Claudia Winklmayr, Vanessa Emanuela Guarino, Christoph Karg, Xiaoyan Yu, Nora Koreuber, Jan Philipp Albrecht, Philip Bischoff, Dagmar Kainmueller:
Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification. - Ran Xie, Rina Barber, Emmanuel J. Candès:
Boosted Conformal Prediction Intervals. - Yivan Zhang, Masashi Sugiyama:
Enriching Disentanglement: From Logical Definitions to Quantitative Metrics. - Herman Bergström, Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson:
Active preference learning for ordering items in- and out-of-sample. - Kaiqu Liang, Zixu Zhang, Jaime F. Fisac:
Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity. - Farzaneh Taleb, Miguel Vasco, Antônio H. Ribeiro, Mårten Björkman, Danica Kragic:
Can Transformers Smell Like Humans? - Aleksandar Petrov, Tom A. Lamb, Alasdair Paren, Philip Torr, Adel Bibi:
Universal In-Context Approximation By Prompting Fully Recurrent Models. - Andrei Margeloiu, Xiangjian Jiang, Nikola Simidjievski, Mateja Jamnik:
TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models. - Rui Huang, Henry Zheng, Yan Wang, Zhuofan Xia, Marco Pavone, Gao Huang:
Training an Open-Vocabulary Monocular 3D Detection Model without 3D Data. - Samuel Holt, Tennison Liu, Mihaela van der Schaar:
Automatically Learning Hybrid Digital Twins of Dynamical Systems. - Shangqian Gao, Chi-Heng Lin, Ting Hua, Zheng Tang, Yilin Shen, Hongxia Jin, Yen-Chang Hsu:
DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models. - Xuan-Hao Liu, Yan-Kai Liu, Yansen Wang, Kan Ren, Hanwen Shi, Zilong Wang, Dongsheng Li, Bao-Liang Lu, Wei-Long Zheng:
EEG2Video: Towards Decoding Dynamic Visual Perception from EEG Signals. - Taiki Miyagawa, Takeru Yokota:
Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees. - Chen Song, Zhenxiao Liang, Bo Sun, Qixing Huang:
PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond. - Shohei Taniguchi, Keno Harada, Gouki Minegishi, Yuta Oshima, Seong Cheol Jeong, Go Nagahara, Tomoshi Iiyama, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo:
ADOPT: Modified Adam Can Converge with Any β2 with the Optimal Rate. - Xufeng Cai, Cheuk Yin Lin, Jelena Diakonikolas:
Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective. - Maximilian Herde, Bogdan Raonic, Tobias Rohner, Roger Käppeli, Roberto Molinaro, Emmanuel de Bézenac, Siddhartha Mishra:
Poseidon: Efficient Foundation Models for PDEs. - Masahito Uwamichi, Simon K. Schnyder, Tetsuya J. Kobayashi, Satoshi Sawai:
Integrating GNN and Neural ODEs for Estimating Non-Reciprocal Two-Body Interactions in Mixed-Species Collective Motion. - Maria-Florina Balcan, Christopher Seiler, Dravyansh Sharma:
Accelerating ERM for data-driven algorithm design using output-sensitive techniques. - Sili Huang, Jifeng Hu, Zhejian Yang, Liwei Yang, Tao Luo, Hechang Chen, Lichao Sun, Bo Yang:
Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling. - Lorenzo Tiberi, Francesca Mignacco, Kazuki Irie, Haim Sompolinsky:
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers. - Jie Hu, Yi-Ting Ma, Do Young Eun:
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD. - Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng:
Generative Retrieval Meets Multi-Graded Relevance. - Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork:
Order-Independence Without Fine Tuning. - Yixia Li, Boya Xiong, Guanhua Chen, Yun Chen:
SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation. - Yihan Wang, Yifan Zhu, Xiao-Shan Gao:
Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously. - Tongxin Li, Tinashe Handina, Shaolei Ren, Adam Wierman:
Safe Exploitative Play with Untrusted Type Beliefs. - Beyazit Yalcinkaya, Niklas Lauffer, Marcell Vazquez-Chanlatte, Sanjit Seshia:
Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning. - Jiechao Guan, Hui Xiong:
Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms. - Kaiwen Dong, Zhichun Guo, Nitesh V. Chawla:
Pure Message Passing Can Estimate Common Neighbor for Link Prediction. - Jiayun Wu, Jiashuo Liu, Peng Cui, Steven Wu:
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift. - Ziqi Gao, Zijing Liu, Yu Li, Jia Li:
Towards Stable Representations for Protein Interface Prediction. - Haohui Wang, Weijie Guan, Jianpeng Chen, Zi Wang, Dawei Zhou:
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox. - Morris Yau, Nikolaos Karalias, Eric Lu, Jessica Xu, Stefanie Jegelka:
Are Graph Neural Networks Optimal Approximation Algorithms? - Javier Maass Martínez, Joaquín Fontbona:
Symmetries in Overparametrized Neural Networks: A Mean Field View. - Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu:
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning. - Zihao Wang, Shaofei Cai, Zhancun Mu, Haowei Lin, Ceyao Zhang, Xuejie Liu, Qing Li, Anji Liu, Xiaojian (Shawn) Ma, Yitao Liang:
OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents. - Jianda Chen, Wen Zheng Terence Ng, Zichen Chen, Sinno Jialin Pan, Tianwei Zhang:
State Chrono Representation for Enhancing Generalization in Reinforcement Learning. - Robin Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Mennatallah El-Assady, Ryan Cotterell:
On Affine Homotopy between Language Encoders. - Huizhuo Yuan, Zixiang Chen, Kaixuan Ji, Quanquan Gu:
Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation. - Eeshaan Jain, Indradyumna Roy, Saswat Meher, Soumen Chakrabarti, Abir De:
Graph Edit Distance with General Costs Using Neural Set Divergence. - Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip Torr, Lewis Hammond, Christian Schröder de Witt:
Secret Collusion among AI Agents: Multi-Agent Deception via Steganography. - Zhongkai Shangguan, Zanming Huang, Eshed Ohn-Bar, Ola Ozernov-Palchik, Derek Kosty, Michael Stoolmiller, Hank Fien:
Scalable Early Childhood Reading Performance Prediction. - Tim Large, Yang Liu, Jacob Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein:
Scalable Optimization in the Modular Norm. - Henry Li, Marcus Pereira:
Solving Inverse Problems via Diffusion Optimal Control. - Terufumi Morishita, Gaku Morio, Atsuki Yamaguchi, Yasuhiro Sogawa:
Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus. - Jiawei Ge, Debarghya Mukherjee, Jianqing Fan:
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift. - Anqi Mao, Mehryar Mohri, Yutao Zhong:
Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer. - Weiyi Xue, Zehan Zheng, Fan Lu, Haiyun Wei, Guang Chen, Changjun Jiang:
GeoNLF: Geometry guided Pose-Free Neural LiDAR Fields. - Seyed Amir Saberi, Amir Najafi, Amin Behjati, Ala Emrani, Yasaman Zolfimoselo, Mahdi Shadrooy, Abolfazl S. Motahari, Babak H. Khalaj:
Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization. - Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik, Guillaume Rabusseau:
Efficient Leverage Score Sampling for Tensor Train Decomposition. - Sachin Garg, Kevin Tan, Michal Derezinski:
Distributed Least Squares in Small Space via Sketching and Bias Reduction. - Seongyun Lee, Sue Hyun Park, Seungone Kim, Minjoon Seo:
Aligning to Thousands of Preferences via System Message Generalization. - Lang Yin, Han Zhao:
On the Expressive Power of Tree-Structured Probabilistic Circuits. - Qianxiong Xu, Xuanyi Liu, Lanyun Zhu, Guosheng Lin, Cheng Long, Ziyue Li, Rui Zhao:
Hybrid Mamba for Few-Shot Segmentation. - Yu Gui, Ying Jin, Zhimei Ren:
Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees. - Zhan Zhuang, Yulong Zhang, Xuehao Wang, Jiangang Lu, Ying Wei, Yu Zhang:
Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models. - Grigory Bartosh, Dmitry P. Vetrov, Christian Andersson Naesseth:
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling. - Jieneng Chen, Luoxin Ye, Ju He, Zhaoyang Wang, Daniel Khashabi, Alan L. Yuille:
Efficient Large Multi-modal Models via Visual Context Compression. - Taisuke Yasuda, Kyriakos Axiotis, Gang Fu, Mohammad Hossein Bateni, Vahab Mirrokni:
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization. - Sam Hawke, Yueen Ma, Didong Li:
Contrastive dimension reduction: when and how? - Tiansheng Huang, Sihao Hu, Ling Liu:
Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attack. - Ameya Prabhu, Vishaal Udandarao, Philip Torr, Matthias Bethge, Adel Bibi, Samuel Albanie:
Efficient Lifelong Model Evaluation in an Era of Rapid Progress. - Shengfang Zhai, Huanran Chen, Yinpeng Dong, Jiajun Li, Qingni Shen, Yansong Gao, Hang Su, Yang Liu:
Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy. - Vijay Ekambaram, Arindam Jati, Pankaj Dayama, Sumanta Mukherjee, Nam Nguyen, Wesley M. Gifford, Chandra Reddy, Jayant Kalagnanam:
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series. - Gunshi Gupta, Karmesh Yadav, Yarin Gal, Dhruv Batra, Zsolt Kira, Cong Lu, Tim G. J. Rudner:
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control. - Hyun-Kurl Jang, Jihun Kim, Hyeokjun Kweon, Kuk-Jin Yoon:
TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight. - Xing Xi, Yangyang Huang, Zhijie Zhong, Ronghua Luo:
UMB: Understanding Model Behavior for Open-World Object Detection. - Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin, Julia E. Vogt, Babak Shahbaba, Stephan Mandt:
Unity by Diversity: Improved Representation Learning for Multimodal VAEs. - Jiahao Li, Yang Lu, Yuan Xie, Yanyun Qu:
Relationship Prompt Learning is Enough for Open-Vocabulary Semantic Segmentation. - Chang Ma, Junlei Zhang, Zhihao Zhu, Cheng Yang, Yujiu Yang, Yaohui Jin, Zhenzhong Lan, Lingpeng Kong, Junxian He:
AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents. - Hyeonggeun Han, Sehwan Kim, Hyungjun Joo, Sangwoo Hong, Jungwoo Lee:
Mitigating Spurious Correlations via Disagreement Probability. - Panwang Pan, Zhuo Su, Chenguo Lin, Zhen Fan, Yongjie Zhang, Zeming Li, Tingting Shen, Yadong Mu, Yebin Liu:
HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors. - Róbert Csordás, Piotr Piekos, Kazuki Irie, Jürgen Schmidhuber:
SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention. - Xuanjia Zhao, Jian Guan, Congyi Fan, Dongli Xu, Youtian Lin, Haiwei Pan, Pengming Feng:
FastDrag: Manipulate Anything in One Step. - Jiequan Cui, Zhuotao Tian, Zhisheng Zhong, Xiaojuan Qi, Bei Yu, Hanwang Zhang:
Decoupled Kullback-Leibler Divergence Loss. - Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvári, Dale Schuurmans:
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates. - Syamantak Kumar, Purnamrita Sarkar:
Oja's Algorithm for Streaming Sparse PCA. - Elita A. Lobo, Justin Payan, Cyrus Cousins, Yair Zick:
Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty. - Hao-Lun Hsu, Weixin Wang, Miroslav Pajic, Pan Xu:
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning. - Edward Milsom, Ben Anson, Laurence Aitchison:
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines. - Gengmo Zhou, Zhen Wang, Feng Yu, Guolin Ke, Zhewei Wei, Zhifeng Gao:
S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search. - Mohit Yadav, Cameron Musco, Daniel R. Sheldon:
Gaussian Process Bandits for Top-k Recommendations. - Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas:
Universal Rates for Active Learning. - Xiangzhe Kong, Yinjun Jia, Wenbing Huang, Yang Liu:
Full-Atom Peptide Design with Geometric Latent Diffusion. - Chi-Wei Hsiao, Yu-Lun Liu, Cheng-Kun Yang, Sheng-Po Kuo, Kevin Jou, Chia-Ping Chen:
ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration. - Zheng Wang, Geyong Min, Wenjie Ruan:
The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions. - Si-An Chen, Lesly Miculicich, Julian Eisenschlos, Zifeng Wang, Zilong Wang, Yanfei Chen, Yasuhisa Fujii, Hsuan-Tien Lin, Chen-Yu Lee, Tomas Pfister:
TableRAG: Million-Token Table Understanding with Language Models. - Ziyi Wang, Yanbo Wang, Xumin Yu, Jie Zhou, Jiwen Lu:
XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation. - Chengming Xu, Chen Liu, Yikai Wang, Yuan Yao, Yanwei Fu:
Towards Global Optimal Visual In-Context Learning Prompt Selection. - Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause:
NeoRL: Efficient Exploration for Nonepisodic RL. - Bowen Wang, Jiuyang Chang, Yiming Qian, Guoxin Chen, Junhao Chen, Zhouqiang Jiang, Jiahao Zhang, Yuta Nakashima, Hajime Nagahara:
DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models. - Adam S. Shai, Lucas Teixeira, Alexander Gietelink Oldenziel, Sarah Marzen, Paul M. Riechers:
Transformers Represent Belief State Geometry in their Residual Stream. - Junhao Cai, Yuji Yang, Weihao Yuan, Yisheng He, Zilong Dong, Liefeng Bo, Hui Cheng, Qifeng Chen:
GIC: Gaussian-Informed Continuum for Physical Property Identification and Simulation. - Jiahang Cao, Mingyuan Sun, Ziqing Wang, Hao Cheng, Qiang Zhang, Shibo Zhou, Renjing Xu:
Spiking Neural Network as Adaptive Event Stream Slicer. - Shenghe Zheng, Hongzhi Wang, Xianglong Liu:
IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors. - Xinyang Li, Zhangyu Lai, Linning Xu, Yansong Qu, Liujuan Cao, Shengchuan Zhang, Bo Dai, Rongrong Ji:
Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text. - Liad Erez, Alon Peled-Cohen, Tomer Koren, Yishay Mansour, Shay Moran:
Fast Rates for Bandit PAC Multiclass Classification. - Feihong Shen, Chao Li, Yifeng Geng, Yongjian Deng, Hao Chen:
Prune and Repaint: Content-Aware Image Retargeting for any Ratio. - Sebastian Dittert, Vincent Moens, Gianni De Fabritiis:
BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO. - Zachary Kenton, Noah Y. Siegel, János Kramár, Jonah Brown-Cohen, Samuel Albanie, Jannis Bulian, Rishabh Agarwal, David Lindner, Yunhao Tang, Noah D. Goodman, Rohin Shah:
On scalable oversight with weak LLMs judging strong LLMs. - Paul-Antoine Le Tolguenec, Yann Besse, Florent Teichteil-Königsbuch, Dennis Wilson, Emmanuel Rachelson:
Exploration by Learning Diverse Skills through Successor State Representations. - Zeyuan Wang, Keyan Ding, Ming Qin, Xiaotong Li, Xiang Zhuang, Yu Zhao, Jianhua Yao, Qiang Zhang, Huajun Chen:
DePLM: Denoising Protein Language Models for Property Optimization. - Yicheng Xiao, Lin Song, Shaoli Huang, Jiangshan Wang, Siyu Song, Yixiao Ge, Xiu Li, Ying Shan:
MambaTree: Tree Topology is All You Need in State Space Model. - Aoran Wang, Jun Pang:
Structural Inference of Dynamical Systems with Conjoined State Space Models. - Jiayu Wang, Yifei Ming, Zhenmei Shi, Vibhav Vineet, Xin Wang, Sharon Li, Neel Joshi:
Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models. - Kai Jiang, Jiaxing Huang, Weiying Xie, Jie Lei, Yunsong Li, Ling Shao, Shijian Lu:
Domain Adaptation for Large-Vocabulary Object Detectors. - Jianhua Sun, Yuxuan Li, Longfei Xu, Nange Wang, Jiude Wei, Yining Zhang, Cewu Lu:
ConceptFactory: Facilitate 3D Object Knowledge Annotation with Object Conceptualization. - Ruiqi Gao, Aleksander Holynski, Philipp Henzler, Arthur Brussee, Ricardo Martin-Brualla, Pratul P. Srinivasan, Jonathan T. Barron, Ben Poole:
CAT3D: Create Anything in 3D with Multi-View Diffusion Models. - Timothée Devergne, Vladimir Kostic, Michele Parrinello, Massimiliano Pontil:
From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach. - Yifan Zhong, Chengdong Ma, Xiaoyuan Zhang, Ziran Yang, Haojun Chen, Qingfu Zhang, Siyuan Qi, Yaodong Yang:
Panacea: Pareto Alignment via Preference Adaptation for LLMs. - Xiaoxuan Gong, Jie Ma:
IR-CM: The Fast and General-purpose Image Restoration Method Based on Consistency Model. - Fan Chen, Dylan J. Foster, Yanjun Han, Jian Qian, Alexander Rakhlin, Yunbei Xu:
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability. - Lanqing Li, Hai Zhang, Xinyu Zhang, Shatong Zhu, Yang Yu, Junqiao Zhao, Pheng-Ann Heng:
Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning. - Ziyuan Huang, Kaixiang Ji, Biao Gong, Zhiwu Qing, Qinglong Zhang, Kecheng Zheng, Jian Wang, Jingdong Chen, Ming Yang:
Accelerating Pre-training of Multimodal LLMs via Chain-of-Sight. - Jiachen Li, Weixi Feng, Tsu-Jui Fu, Xinyi Wang, Sugato Basu, Wenhu Chen, William Yang Wang:
T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback. - Rafid Mahmood:
Pricing and Competition for Generative AI. - Jize Wang, Zerun Ma, Yining Li, Songyang Zhang, Cailian Chen, Kai Chen, Xinyi Le:
GTA: A Benchmark for General Tool Agents. - Jiajun He, Gergely Flamich, José Miguel Hernández-Lobato:
Accelerating Relative Entropy Coding with Space Partitioning. - Qi Bi, Jingjun Yi, Hao Zheng, Wei Ji, Haolan Zhan, Yawen Huang, Yuexiang Li, Yefeng Zheng:
Samba: Severity-aware Recurrent Modeling for Cross-domain Medical Image Grading. - Sunny Panchal, Apratim Bhattacharyya, Guillaume Berger, Antoine Mercier, Cornelius Böhm, Florian Dietrichkeit, Reza Pourreza, Xuanlin Li, Pulkit Madan, Mingu Lee, Mark Todorovich, Ingo Bax, Roland Memisevic:
What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction. - Tiago da Silva, Eliezer de Souza da Silva, Diego Mesquita:
On Divergence Measures for Training GFlowNets. - Hojung Jung, Youngrok Park, Laura Schmid, Jaehyeong Jo, Dongkyu Lee, Bongsang Kim, Se-Young Yun, Jinwoo Shin:
Conditional Synthesis of 3D Molecules with Time Correction Sampler. - Gabriel Sarch, Lawrence Jang, Michael J. Tarr, William W. Cohen, Kenneth Marino, Katerina Fragkiadaki:
VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought. - Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli:
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs. - Xiyuan Li, Youjun Wang, Weiwei Liu:
The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems. - Weiguo Pian, Yiyang Nan, Shijian Deng, Shentong Mo, Yunhui Guo, Yapeng Tian:
Continual Audio-Visual Sound Separation. - Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin:
Amortizing intractable inference in diffusion models for vision, language, and control. - Zeqi Xiao, Yifan Zhou, Shuai Yang, Xingang Pan:
Video Diffusion Models are Training-free Motion Interpreter and Controller. - Tian Tian, Lin Yang, Csaba Szepesvári:
Confident Natural Policy Gradient for Local Planning in qπ-realizable Constrained MDPs. - Dongzhi Jiang, Guanglu Song, Xiaoshi Wu, Renrui Zhang, Dazhong Shen, Zhuofan Zong, Yu Liu, Hongsheng Li:
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching. - Renato Paes Leme, Georgios Piliouras, Jon Schneider:
Convergence of No-Swap-Regret Dynamics in Self-Play. - Alexander Hägele, Elie Bakouch, Atli Kosson, Loubna Ben Allal, Leandro von Werra, Martin Jaggi:
Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations. - Haowen Dou, Lujuan Dang, Zhirong Luan, Badong Chen:
Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration. - Ziyi Wu, Yulia Rubanova, Rishabh Kabra, Drew A. Hudson, Igor Gilitschenski, Yusuf Aytar, Sjoerd van Steenkiste, Kelsey R. Allen, Thomas Kipf:
Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models. - Guangzhao Cheng, Chengbo Fu, Lu Cheng:
NanoBaseLib: A Multi-Task Benchmark Dataset for Nanopore Sequencing. - Yan Fan, Yu Wang, Pengfei Zhu, Dongyue Chen, Qinghua Hu:
Persistence Homology Distillation for Semi-supervised Continual Learning. - Meng Wei, Qianyi Wu, Jianmin Zheng, Hamid Rezatofighi, Jianfei Cai:
Normal-GS: 3D Gaussian Splatting with Normal-Involved Rendering. - Yijun Yang, Ruiyuan Gao, Xiao Yang, Jianyuan Zhong, Qiang Xu:
GuardT2I: Defending Text-to-Image Models from Adversarial Prompts. - Francesco Bacchiocchi, Matteo Bollini, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Online Bayesian Persuasion Without a Clue. - Jacopo Teneggi, Jeremias Sulam:
Testing Semantic Importance via Betting. - Bruno Andreis, Bedionita Soro, Philip H. S. Torr, Sung Ju Hwang:
Set-based Neural Network Encoding Without Weight Tying. - Jiaheng Hu, Zizhao Wang, Peter Stone, Roberto Martín-Martín:
Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning. - David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, Jan-Jakob Sonke, Erik J. Bekkers, Efstratios Gavves:
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields. - Brianna Karpowicz, Joel Ye, Chaofei Fan, Pablo Tostado-Marcos, Fabio Rizzoglio, Clayton Washington, Thiago Scodeler, Diogo de Lucena, Samuel R. Nason-Tomaszewski, Matthew Mender, Xuan Ma, Ezequiel M. Arneodo, Leigh R. Hochberg, Cynthia A. Chestek, Jaimie M. Henderson, Timothy Gentner, Vikash Gilja, Lee E. Miller, Adam Rouse, Robert Gaunt, Jennifer L. Collinger, Chethan Pandarinath:
Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark. - Shufan Shen, Junshu Sun, Xiangyang Ji, Qingming Huang, Shuhui Wang:
Expanding Sparse Tuning for Low Memory Usage. - Wooseong Cho, Taehyun Hwang, Joongkyu Lee, Min-hwan Oh:
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation. - Zhongkai Hao, Jiachen Yao, Chang Su, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, Jun Zhu:
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs. - Yang Sui, Yanyu Li, Anil Kag, Yerlan Idelbayev, Junli Cao, Ju Hu, Dhritiman Sagar, Bo Yuan, Sergey Tulyakov, Jian Ren:
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model. - Yunze Man, Shuhong Zheng, Zhipeng Bao, Martial Hebert, Liangyan Gui, Yu-Xiong Wang:
Lexicon3D: Probing Visual Foundation Models for Complex 3D Scene Understanding. - Pierre Marion, Lénaïc Chizat:
Deep linear networks for regression are implicitly regularized towards flat minima. - Robby Costales, Stefanos Nikolaidis:
Enabling Adaptive Agent Training in Open-Ended Simulators by Targeting Diversity. - Rishabh Agarwal, Avi Singh, Lei Zhang, Bernd Bohnet, Luis Rosias, Stephanie C. Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle:
Many-Shot In-Context Learning. - Beier Zhu, Jiequan Cui, Hanwang Zhang:
Robust Fine-tuning of Zero-shot Models via Variance Reduction. - Mahdi Karami, Ali Ghodsi:
Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling. - Pengfei Yao, Yinglong Zhu, Huikun Bi, Tianlu Mao, Zhaoqi Wang:
TrajCLIP: Pedestrian trajectory prediction method using contrastive learning and idempotent networks. - Connor Mclaughlin, Lili Su:
Personalized Federated Learning via Feature Distribution Adaptation. - Xuanfa Jin, Ziyan Wang, Yali Du, Meng Fang, Haifeng Zhang, Jun Wang:
Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf. - Xiangchen Song, Zijian Li, Guangyi Chen, Yujia Zheng, Yewen Fan, Xinshuai Dong, Kun Zhang:
Causal Temporal Representation Learning with Nonstationary Sparse Transition. - Zihui Xue, Romy Luo, Changan Chen, Kristen Grauman:
HOI-Swap: Swapping Objects in Videos with Hand-Object Interaction Awareness. - Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison:
End-To-End Causal Effect Estimation from Unstructured Natural Language Data. - Zi Yang, Ziyue Liu, Samridhi Choudhary, Xinfeng Xie, Cao Gao, Siegfried Kunzmann, Zheng Zhang:
CoMERA: Computing- and Memory-Efficient Training via Rank-Adaptive Tensor Optimization. - Ipsita Ghosh, Abiy Tasissa, Christian Kümmerle:
Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization. - Md. Musfiqur Rahman, Matt Jordan, Murat Kocaoglu:
Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand. - Kazusato Oko, Yujin Song, Taiji Suzuki, Denny Wu:
Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context. - Guru Guruganesh, Yoav Kolumbus, Jon Schneider, Inbal Talgam-Cohen, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Joshua R. Wang, S. Matthew Weinberg:
Contracting with a Learning Agent. - Zhenwei Lin, Qi Deng:
Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints. - Alvin W. M. Tan, Chunhua Yu, Bria Long, Wanjing Ma, Tonya Murray, Rebecca D. Silverman, Jason D. Yeatman, Michael C. Frank:
DevBench: A multimodal developmental benchmark for language learning. - Jianming Pan, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian:
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning. - Francisco M. Castro-Macías, Pablo Morales-Alvarez, Yunan Wu, Rafael Molina, Aggelos K. Katsaggelos:
Sm: enhanced localization in Multiple Instance Learning for medical imaging classification. - Seok-Jin Kim, Min-hwan Oh:
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit. - Ashwin Ramachandran, Vaibhav Raj, Indradyumna Roy, Soumen Chakrabarti, Abir De:
Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval. - Renyuan Li, Zhehui Chen, Guanyi Wang:
Solving Sparse \& High-Dimensional-Output Regression via Compression. - Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra:
Relational Concept Bottleneck Models. - Adrien Le-Coz, Stéphane Herbin, Faouzi Adjed:
Confidence Calibration of Classifiers with Many Classes. - Manel Rodriguez-Soto, Juan A. Rodríguez-Aguilar, Maite López-Sánchez:
An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning. - Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone:
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. - Jianqing Xu, Shen Li, Jiaying Wu, Miao Xiong, Ailin Deng, Jiazhen Ji, Yuge Huang, Guodong Mu, Wenjie Feng, Shouhong Ding, Bryan Hooi:
ID3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition. - Haoyi Zhu, Yating Wang, Di Huang, Weicai Ye, Wanli Ouyang, Tong He:
Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning. - Junkai Xia, Chenxin Xu, Qingyao Xu, Yanfeng Wang, Siheng Chen:
Language-Driven Interactive Traffic Trajectory Generation. - Guangyan Chen, Meiling Wang, Te Cui, Yao Mu, Haoyang Lu, Tianxing Zhou, Zicai Peng, Mengxiao Hu, Haizhou Li, Li Yuan, Yi Yang, Yufeng Yue:
VLMimic: Vision Language Models are Visual Imitation Learner for Fine-grained Actions. - Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash:
Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis. - Rui Min, Zeyu Qin, Nevin L. Zhang, Li Shen, Minhao Cheng:
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense. - Yu Zhong, Xiao Wu, Liang-Jian Deng, Zihan Cao, Hong-Xia Dou:
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening. - Simon Wagner, Leif Seute, Vsevolod Viliuga, Nicolas Wolf, Frauke Gräter, Jan Stühmer:
Generating Highly Designable Proteins with Geometric Algebra Flow Matching. - Bowen Xu, Yiwen Huang, Chuan Hong, Shuangning Li, Molei Liu:
Covariate Shift Corrected Conditional Randomization Test. - Alex Mathai, Chenxi Huang, Petros Maniatis, Aleksandr Nogikh, Franjo Ivancic, Junfeng Yang, Baishakhi Ray:
kGym: A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution. - Xiaoyue Wan, Zhuo Chen, Bingzhi Duan, Xu Zhao:
Dual-Diffusion for Binocular 3D Human Pose Estimation. - Junho Myung, Nayeon Lee, Yi Zhou, Jiho Jin, Rifki Afina Putri, Dimosthenis Antypas, Hsuvas Borkakoty, Eunsu Kim, Carla Pérez-Almendros, Abinew Ali Ayele, Víctor Gutiérrez-Basulto, Yazmín Ibáñez-García, Hwaran Lee, Shamsuddeen Hassan Muhammad, Ki-Woong Park, Anar Rzayev, Nina White, Seid Muhie Yimam, Mohammad Taher Pilehvar, Nedjma Ousidhoum, José Camacho-Collados, Alice Oh:
BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages. - Nan Song, Bozhou Zhang, Xiatian Zhu, Li Zhang:
Motion Forecasting in Continuous Driving. - Shuguang Yu, Shuxing Fang, Ruixin Peng, Zhengling Qi, Fan Zhou, Chengchun Shi:
Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning. - Xiaochuan Gong, Jie Hao, Mingrui Liu:
An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness. - Arijit Sehanobish, Kumar Avinava Dubey, Krzysztof Marcin Choromanski, Somnath Basu Roy Chowdhury, Deepali Jain, Vikas Sindhwani, Snigdha Chaturvedi:
Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning. - Stephen Pasteris, Chris Hicks, Vasilios Mavroudis, Mark Herbster:
Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously. - Yonggan Fu, Zhongzhi Yu, Junwei Li, Jiayi Qian, Yongan Zhang, Xiangchi Yuan, Dachuan Shi, Roman Yakunin, Yingyan (Celine) Lin:
AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment. - Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni:
Understanding Transformer Reasoning Capabilities via Graph Algorithms. - Yiyue Li, Shaoting Zhang, Kang Li, Qicheng Lao:
One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection. - Thibault Simonetto, Salah Ghamizi, Maxime Cordy:
TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases. - Juan Jose Garau-Luis, Patrick Bordes, Liam Gonzalez, Masa Roller, Bernardo P. de Almeida, Christopher Blum, Lorenz Hexemer, Stefan Laurent, Maren Lang, Thomas Pierrot, Guillaume Richard:
Multi-modal Transfer Learning between Biological Foundation Models. - Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao:
OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning. - Eszter Székely, Lorenzo Bardone, Federica Gerace, Sebastian Goldt:
Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks. - Jan Schuchardt, Mihail Stoian, Arthur Kosmala, Stephan Günnemann:
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification. - Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, Jiashi Feng:
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator. - Orin Levy, Noam Touitou, Aviv Rosenberg:
Online Weighted Paging with Unknown Weights. - Jiashuo Jiang, Yinyu Ye:
Achieving Õ(1/ε) Sample Complexity for Constrained Markov Decision Process. - Andrew Wagenmaker, Kevin Huang, Liyiming Ke, Kevin G. Jamieson, Abhishek Gupta:
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL. - Yinuo Jing, Ruxu Zhang, Kongming Liang, Yongxiang Li, Zhongjiang He, Zhanyu Ma, Jun Guo:
Animal-Bench: Benchmarking Multimodal Video Models for Animal-centric Video Understanding. - Akhil Jalan, Arya Mazumdar, Soumendu Sundar Mukherjee, Purnamrita Sarkar:
Transfer Learning for Latent Variable Network Models. - Haoming Wang, Zhaoming Tian, Yunpeng Song, Xiangliang Zhang, Zhongmin Cai:
Beyond Single Stationary Policies: Meta-Task Players as Naturally Superior Collaborators. - Wenzhi Fang, Dong-Jun Han, Evan Chen, Shiqiang Wang, Christopher G. Brinton:
Hierarchical Federated Learning with Multi-Timescale Gradient Correction. - Zhenyi Lu, Chenghao Fan, Wei Wei, Xiaoye Qu, Dangyang Chen, Yu Cheng:
Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging. - Dong Zhao, Qi Zang, Shuang Wang, Nicu Sebe, Zhun Zhong:
Connectivity-Driven Pseudo-Labeling Makes Stronger Cross-Domain Segmenters. - Hang Yin, Liyao Xiang, Dong Ding, Yuheng He, Yihan Wu, Pengzhi Chu, Xinbing Wang, Chenghu Zhou:
Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Cases. - Jason Vander Woude, Peter Dixon, Aduri Pavan, Jamie Radcliffe, N. V. Vinodchandran:
Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma. - Seohong Park, Kevin Frans, Sergey Levine, Aviral Kumar:
Is Value Learning Really the Main Bottleneck in Offline RL? - Divyansh Srivastava, Ge Yan, Lily Weng:
VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance. - Yiqi Jiang, Hakki O. Akengin, Ji Zhou, Mehmet Aslihak, Yang Li, Radoslaw Chrapkiewicz, Oscar Hernandez, Sadegh Ebrahimi, Omar Jaidar, Yanping Zhang, Hakan Inan, Christopher Miranda, Fatih Dinc, Marta Blanco-Pozo, Mark J. Schnitzer:
ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets. - Dmitry Yarotsky:
Learnability of high-dimensional targets by two-parameter models and gradient flow. - Ye Sun, Hao Zhang, Tiehua Zhang, Xingjun Ma, Yu-Gang Jiang:
UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation. - Michael Huang, Vishal Gupta:
Decision-Focused Learning with Directional Gradients. - Dongchen Han, Yifan Pu, Zhuofan Xia, Yizeng Han, Xuran Pan, Xiu Li, Jiwen Lu, Shiji Song, Gao Huang:
Bridging the Divide: Reconsidering Softmax and Linear Attention. - Tobias Schröder, Zijing Ou, Yingzhen Li, Andrew B. Duncan:
Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces. - Jiaxing Zhang, Zhuomin Chen, Hao Mei, Longchao Da, Dongsheng Luo, Hua Wei:
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks. - Ilija Radosavovic, Bike Zhang, Baifeng Shi, Jathushan Rajasegaran, Sarthak Kamat, Trevor Darrell, Koushil Sreenath, Jitendra Malik:
Humanoid Locomotion as Next Token Prediction. - Chongming Liu, Jingyang Ma, Songting Li, Douglas Zhou:
Dendritic Integration Inspired Artificial Neural Networks Capture Data Correlation. - Ruiqi Zhong, Heng Wang, Dan Klein, Jacob Steinhardt:
Explaining Datasets in Words: Statistical Models with Natural Language Parameters. - Seta Rakotomandimby, Jean-Philippe Chancelier, Michel De Lara, Mathieu Blondel:
Learning with Fitzpatrick Losses. - Yubin Kim, Chanwoo Park, Hyewon Jeong, Yik Siu Chan, Xuhai Xu, Daniel McDuff, Hyeonhoon Lee, Marzyeh Ghassemi, Cynthia Breazeal, Hae Won Park:
MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making. - Jason Gross, Rajashree Agrawal, Thomas Kwa, Euan Ong, Chun Hei Yip, Alex Gibson, Soufiane Noubir, Lawrence Chan:
Compact Proofs of Model Performance via Mechanistic Interpretability. - Lixu Wang, Xinyu Du, Qi Zhu:
Semantic Feature Learning for Universal Unsupervised Cross-Domain Retrieval. - Kaizheng Wang, Fabio Cuzzolin, Shireen Kudukkil Manchingal, Keivan Shariatmadar, David Moens, Hans Hallez:
Credal Deep Ensembles for Uncertainty Quantification. - Hongzhan Lin, Ang Lv, Yuhan Chen, Chen Zhu, Yang Song, Hengshu Zhu, Rui Yan:
Mixture of In-Context Experts Enhance LLMs' Long Context Awareness. - Zikang Zhou, Haibo Hu, Xinhong Chen, Jianping Wang, Nan Guan, Kui Wu, Yung-Hui Li, Yu-Kai Huang, Chun Jason Xue:
BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction. - Yuhang Lu, Xinge Zhu, Tai Wang, Yuexin Ma:
OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queries. - Qi Chen, Bowen Zhang, Gang Wang, Qi Wu:
Weak-eval-Strong: Evaluating and Eliciting Lateral Thinking of LLMs with Situation Puzzles. - Eli Chien, Haoyu Wang, Ziang Chen, Pan Li:
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning. - Zhe Xu, Ruizhong Qiu, Yuzhong Chen, Huiyuan Chen, Xiran Fan, Menghai Pan, Zhichen Zeng, Mahashweta Das, Hanghang Tong:
Discrete-state Continuous-time Diffusion for Graph Generation. - Jiawei Gao, Ziqin Wang, Zeqi Xiao, Jingbo Wang, Tai Wang, Jinkun Cao, Xiaolin Hu, Si Liu, Jifeng Dai, Jiangmiao Pang:
CooHOI: Learning Cooperative Human-Object Interaction with Manipulated Object Dynamics. - Xin Zou, Zhengyu Zhou, Jingyuan Xu, Weiwei Liu:
A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers. - Yizhen Luo, Zikun Nie, Massimo Hong, Suyuan Zhao, Hao Zhou, Zaiqing Nie:
MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering. - Arseny Skryagin, Felix Divo, Mohammad Amin Ali, Devendra Singh Dhami, Kristian Kersting:
Graph Neural Networks Need Cluster-Normalize-Activate Modules. - Yun-Yen Chuang, Hung-Min Hsu, Kevin Lin, Chen-Sheng Gu, Ling Zhen Li, Ray-I Chang, Hung-yi Lee:
Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-Exploration. - Xiaodi Li, Zongxin Yang, Ruijie Quan, Yi Yang:
DRIP: Unleashing Diffusion Priors for Joint Foreground and Alpha Prediction in Image Matting. - Dongfu Jiang, Max Ku, Tianle Li, Yuansheng Ni, Shizhuo Sun, Rongqi Fan, Wenhu Chen:
GenAI Arena: An Open Evaluation Platform for Generative Models. - Jiaan Luo, Feng Hong, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang:
Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation. - Jianqiao Lu, Zhiyang Dou, Hongru Wang, Zeyu Cao, Jianbo Dai, Yunlong Feng, Zhijiang Guo:
AutoPSV: Automated Process-Supervised Verifier. - Yanyan Huang, Weiqin Zhao, Yihang Chen, Yu Fu, Lequan Yu:
Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement. - Hui Zheng, Haiteng Wang, Wei-Bang Jiang, Zhongtao Chen, Li He, Pei-Yang Lin, Peng-Hu Wei, Guo-Guang Zhao, Yun-Zhe Liu:
Du-IN: Discrete units-guided mask modeling for decoding speech from Intracranial Neural signals. - Luohe Shi, Yao Yao, Zuchao Li, Lefei Zhang, Hai Zhao:
Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models. - Zhenghao Pan, Haijin Zeng, Jiezhang Cao, Yongyong Chen, Kai Zhang, Yong Xu:
MambaSCI: Efficient Mamba-UNet for Quad-Bayer Patterned Video Snapshot Compressive Imaging. - Pramith Devulapalli, Steve Hanneke:
Learning from Snapshots of Discrete and Continuous Data Streams. - Shun Lei, Yixuan Zhou, Boshi Tang, Max W. Y. Lam, Feng Liu, Hangyu Liu, Jingcheng Wu, Shiyin Kang, Zhiyong Wu, Helen Meng:
SongCreator: Lyrics-based Universal Song Generation. - Rong Ma, Jie Chen, Xiangyang Xue, Jian Pu:
Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs. - Chun Gu, Zeyu Yang, Zijie Pan, Xiatian Zhu, Li Zhang:
Tetrahedron Splatting for 3D Generation. - Xin Jin, Pengyi Jiao, Zheng-Peng Duan, Xingchao Yang, Chongyi Li, Chun-Le Guo, Bo Ren:
Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering for HDR View Synthesis. - Junyoung Seo, Kazumi Fukuda, Takashi Shibuya, Takuya Narihira, Naoki Murata, Shoukang Hu, Chieh-Hsin Lai, Seungryong Kim, Yuki Mitsufuji:
GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping. - Yong-Hyun Park, Sangdoo Yun, Jin-Hwa Kim, Junho Kim, Geonhui Jang, Yonghyun Jeong, Junghyo Jo, Gayoung Lee:
Direct Unlearning Optimization for Robust and Safe Text-to-Image Models. - Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar:
Balancing Context Length and Mixing Times for Reinforcement Learning at Scale. - Xiangdong Zhang, Shaofeng Zhang, Junchi Yan:
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders. - Eric Volkmann, Alena Brändle, Daniel Durstewitz, Georgia Koppe:
A scalable generative model for dynamical system reconstruction from neuroimaging data. - Shuai Liu, Boyang Li, Zhiyu Fang, Mingyue Cui, Kai Huang:
FFAM: Feature Factorization Activation Map for Explanation of 3D Detectors. - Qixun Wang, Yifei Wang, Yisen Wang, Xianghua Ying:
Dissecting the Failure of Invariant Learning on Graphs. - Luise Ge, Daniel Halpern, Evi Micha, Ariel D. Procaccia, Itai Shapira, Yevgeniy Vorobeychik, Junlin Wu:
Axioms for AI Alignment from Human Feedback. - Tobias Fischer, Jonas Kulhanek, Samuel Rota Bulò, Lorenzo Porzi, Marc Pollefeys, Peter Kontschieder:
Dynamic 3D Gaussian Fields for Urban Areas. - Yizi Zhang, Yanchen Wang, Donato Jiménez-Benetó, Zixuan Wang, Mehdi Azabou, Blake A. Richards, Renee Tung, Olivier Winter, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole L. Hurwitz:
Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution. - Yi Xin, Siqi Luo, Xuyang Liu, Yuntao Du, Haodi Zhou, Xinyu Cheng, Christina E. Lee, Junlong Du, Haozhe Wang, Mingcai Chen, Ting Liu, Guimin Hu, Zhongwei Wan, Rongchao Zhang, Aoxue Li, Mingyang Yi, Xiaohong Liu:
V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark. - Yunong Liu, Cristóbal Eyzaguirre, Manling Li, Shubh Khanna, Juan Carlos Niebles, Vineeth Ravi, Saumitra Mishra, Weiyu Liu, Jiajun Wu:
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos. - Davide Maran, Francesco Bacchiocchi, Francesco Emanuele Stradi, Matteo Castiglioni, Nicola Gatti, Marcello Restelli:
Bandits with Ranking Feedback. - Qiankun Gao, Jiarui Meng, Chengxiang Wen, Jie Chen, Jian Zhang:
HiCoM: Hierarchical Coherent Motion for Dynamic Streamable Scenes with 3D Gaussian Splatting. - Ruiquan Huang, Yingbin Liang, Jing Yang:
Non-asymptotic Convergence of Training Transformers for Next-token Prediction. - Shaokui Wei, Hongyuan Zha, Baoyuan Wu:
Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor. - Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin:
Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning. - Jerry Wei, Chengrun Yang, Xinying Song, Yifeng Lu, Nathan Hu, Jie Huang, Dustin Tran, Daiyi Peng, Ruibo Liu, Da Huang, Cosmo Du, Quoc V. Le:
Long-form factuality in large language models. - Cong Xu, Jun Wang, Jianyong Wang, Wei Zhang:
Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution. - Zheng Yu, Yaohua Wang, Siying Cui, Aixi Zhang, Wei-Long Zheng, Senzhang Wang:
FuseAnyPart: Diffusion-Driven Facial Parts Swapping via Multiple Reference Images. - Donghwan Kim, Tae-Kyun Kim:
Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded Images. - Xuanqian Wang, Jing Li, Ivor W. Tsang, Yew Soon Ong:
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior. - Junshu Sun, Chenxue Yang, Xiangyang Ji, Qingming Huang, Shuhui Wang:
Towards Dynamic Message Passing on Graphs. - Shakiba Kheradmand, Daniel Rebain, Gopal Sharma, Weiwei Sun, Yang-Che Tseng, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, Kwang Moo Yi:
3D Gaussian Splatting as Markov Chain Monte Carlo. - Minghan Li, Xilun Chen, Ari Holtzman, Beidi Chen, Jimmy Lin, Scott Yih, Victoria Lin:
Nearest Neighbor Speculative Decoding for LLM Generation and Attribution. - Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin:
Improved off-policy training of diffusion samplers. - Sriram Balasubramanian, Samyadeep Basu, Soheil Feizi:
Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP. - Chen Huang, Skyler Seto, Samira Abnar, David Grangier, Navdeep Jaitly, Joshua M. Susskind:
Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP. - Kun Zhou, Xinyu Lin, Zhonghang Liu, Xiaoguang Han, Jiangbo Lu:
UPS: Unified Projection Sharing for Lightweight Single-Image Super-resolution and Beyond. - Hanwen Zhong, Jiaxin Chen, Yutong Zhang, Di Huang, Yunhong Wang:
Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learner. - Daniel Kunin, Allan Raventós, Clémentine C. J. Dominé, Feng Chen, David A. Klindt, Andrew M. Saxe, Surya Ganguli:
Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning. - Zhuo Zheng, Yanfei Zhong, Liangpei Zhang, Stefano Ermon:
Segment Any Change. - Xun Zhu, Ying Hu, Fanbin Mo, Miao Li, Ji Wu:
Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoE. - Xiaoou Cheng, Jonathan Weare:
The surprising efficiency of temporal difference learning for rare event prediction. - Xun Wu, Shaohan Huang, Guolong Wang, Jing Xiong, Furu Wei:
Multimodal Large Language Models Make Text-to-Image Generative Models Align Better. - Hrithik Ravi, Clayton Scott, Daniel Soudry, Yutong Wang:
The Implicit Bias of Gradient Descent on Separable Multiclass Data. - Junbao Chen, Jingfeng Xue, Yong Wang, Zhenyan Liu, Lu Huang:
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift. - Xin Ma, Yang Liu, Jingjing Liu, Xiaoxu Ma:
Mesa-Extrapolation: A Weave Position Encoding Method for Enhanced Extrapolation in LLMs. - Nemin Wu, Qian Cao, Zhangyu Wang, Zeping Liu, Yanlin Qi, Jielu Zhang, Joshua Ni, Xiaobai Angela Yao, Hongxu Ma, Lan Mu, Stefano Ermon, Tanuja Ganu, Akshay Nambi, Ni Lao, Gengchen Mai:
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning. - Yang Jiao, Shaoxiang Chen, Zequn Jie, Jingjing Chen, Lin Ma, Yu-Gang Jiang:
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Models. - Guowen Zhang, Lue Fan, Chenhang He, Zhen Lei, Zhaoxiang Zhang, Lei Zhang:
Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection. - Xiang Liu, Liangxi Liu, Feiyang Ye, Yunheng Shen, Xia Li, Linshan Jiang, Jialin Li:
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation. - Wei Huang, Andi Han, Yongqiang Chen, Yuan Cao, Zhiqiang Xu, Taiji Suzuki:
On the Comparison between Multi-modal and Single-modal Contrastive Learning. - Weitong Zhang, Chengqi Zang, Liu Li, Sarah Cechnicka, Cheng Ouyang, Bernhard Kainz:
Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics. - Elaine Lau, Stephen Zhewen Lu, Ling Pan, Doina Precup, Emmanuel Bengio:
QGFN: Controllable Greediness with Action Values. - Tianle Zhang, Langtian Ma, Yuchen Yan, Yuchen Zhang, Yue Yang, Ziyao Guo, Wenqi Shao, Kai Wang, Yang You, Yu Qiao, Ping Luo, Kaipeng Zhang:
Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality. - Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu:
Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation. - Shukai Duan, Heng Ping, Nikos Kanakaris, Xiongye Xiao, Panagiotis Kyriakis, Nesreen K. Ahmed, Peiyu Zhang, Guixiang Ma, Mihai Capota, Shahin Nazarian, Theodore L. Willke, Paul Bogdan:
A Structure-Aware Framework for Learning Device Placements on Computation Graphs. - Chenlu Ye, Wei Xiong, Yuheng Zhang, Hanze Dong, Nan Jiang, Tong Zhang:
Online Iterative Reinforcement Learning from Human Feedback with General Preference Model. - Ming Nie, Dan Ding, Chunwei Wang, Yuanfan Guo, Jianhua Han, Hang Xu, Li Zhang:
SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM. - Mohsen Bayati, Yuwei Luo, William Overman, Mohamad Sadegh Shirani Faradonbeh, Ruoxuan Xiong:
Higher-Order Causal Message Passing for Experimentation with Complex Interference. - Niels Mündler, Mark Niklas Müller, Jingxuan He, Martin T. Vechev:
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents. - Sarvar Patel, Giuseppe Persiano, Joon Young Seo, Kevin Yeo:
Differentially Private Set Representations. - Iuliia Dmitrieva, Sergey Babkin, Adam S. Charles:
realSEUDO for real-time calcium imaging analysis. - Pei-Yau Weng, Minh Hoang, Lam M. Nguyen, My T. Thai, Lily Weng, Trong Nghia Hoang:
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data. - Kenny Peng, Nikhil Garg:
Monoculture in Matching Markets. - Hemal Naik, Junran Yang, Dipin Das, Margaret Crofoot, Akanksha Rathore, Vivek Hari Sridhar:
BuckTales: A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes. - Maximilian Stölzle, Cosimo Della Santina:
Input-to-State Stable Coupled Oscillator Networks for Closed-form Model-based Control in Latent Space. - Xiuyu Yang, Yunze Man, Junkun Chen, Yu-Xiong Wang:
SceneCraft: Layout-Guided 3D Scene Generation. - Antoine Maillard, Emanuele Troiani, Simon Martin, Florent Krzakala, Lenka Zdeborová:
Bayes-optimal learning of an extensive-width neural network from quadratically many samples. - Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Luca Foschini, Joan Giner-Miguelez, Pieter Gijsbers, Sujata S. Goswami, Nitisha Jain, Michalis Karamousadakis, Michael Kuchnik, Satyapriya Krishna, Sylvain Lesage, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Hamidah Oderinwale, Pierre Ruyssen, Tim Santos, Rajat Shinde, Elena Simperl, Arjun Suresh, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Susheel Varma, Jos van der Velde, Steffen Vogler, Carole-Jean Wu, Luyao Zhang:
Croissant: A Metadata Format for ML-Ready Datasets. - Skanda Koppula, Ignacio Rocco, Yi Yang, Joseph Heyward, João Carreira, Andrew Zisserman, Gabriel Brostow, Carl Doersch:
TAPVid-3D: A Benchmark for Tracking Any Point in 3D. - Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang:
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context. - Will Ma, Pan Xu:
Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions. - Maya Varma, Jean-Benoit Delbrouck, Zhihong Chen, Akshay Chaudhari, Curtis P. Langlotz:
RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models. - Zhuoshi Pan, Yuguang Yao, Gaowen Liu, Bingquan Shen, H. Vicky Zhao, Ramana Kompella, Sijia Liu:
From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models. - Billy Jin, Thomas Kesselheim, Will Ma, Sahil Singla:
Sample Complexity of Posted Pricing for a Single Item. - Isaac Osafo Nkansah, Neil Gallagher, Ruchi Sandilya, Conor Liston, Logan Grosenick:
Generalizing CNNs to graphs with learnable neighborhood quantization. - Kaichen Huang, Shenghua Wan, Minghao Shao, Hai-Hang Sun, Le Gan, Shuai Feng, De-Chuan Zhan:
Leveraging Separated World Model for Exploration in Visually Distracted Environments. - Junlin He, Jinxiao Du, Susu Xu, Wei Ma:
Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization. - Haider Al-Tahan, Quentin Garrido, Randall Balestriero, Diane Bouchacourt, Caner Hazirbas, Mark Ibrahim:
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling. - Yanlai Yang, Matt Jones, Michael C. Mozer, Mengye Ren:
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training. - Tao Yang, Cuiling Lan, Yan Lu, Nanning Zheng:
Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement. - Anlan Yu, Shusen Jing, Ning Lyu, Wujie Wen, Zhiyuan Yan:
Error Correction Output Codes for Robust Neural Networks against Weight-errors: A Neural Tangent Kernel Point of View. - Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li:
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms. - Mengyuan Chen, Junyu Gao, Changsheng Xu:
Conjugated Semantic Pool Improves OOD Detection with Pre-trained Vision-Language Models. - R. Teal Witter, Christopher Musco:
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm. - Hui Guo, Grace Yi, Boyu Wang:
Learning from Noisy Labels via Conditional Distributionally Robust Optimization. - Yiyang Zhao, Yunzhuo Liu, Bo Jiang, Tian Guo:
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework. - Jiawei Yao, Qi Qian, Juhua Hu:
Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning. - Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni:
RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation. - Jian Liu, Jianyu Wu, Hairun Xie, Guoqing Zhang, Jing Wang, Wei Liu, Wanli Ouyang, Junjun Jiang, Xianming Liu, Shixiang Tang, Miao Zhang:
AFBench: A Large-scale Benchmark for Airfoil Design. - William Bankes, George Hughes, Ilija Bogunovic, Zi Wang:
REDUCR: Robust Data Downsampling using Class Priority Reweighting. - Chenrui Wei, Mengzhou Sun, Wei Wang:
Proving Olympiad Algebraic Inequalities without Human Demonstrations. - Róbert Busa-Fekete, Travis Dick, Claudio Gentile, Andrés Muñoz Medina, Adam D. Smith, Marika Swanberg:
Auditing Privacy Mechanisms via Label Inference Attacks. - Joan Bruna, Jiequn Han:
Provable Posterior Sampling with Denoising Oracles via Tilted Transport. - Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr:
AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. - Yiqin Lv, Qi Wang, Dong Liang, Zheng Xie:
Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning. - Zhimin Chen, Liang Yang, Yingwei Li, Longlong Jing, Bing Li:
SAM-Guided Masked Token Prediction for 3D Scene Understanding. - Seongmin Hong, Suh Yoon Jeon, Kyeonghyun Lee, Ernest K. Ryu, Se Young Chun:
Gradient-free Decoder Inversion in Latent Diffusion Models. - Julieta Martinez, Emily Kim, Javier Romero, Timur M. Bagautdinov, Shunsuke Saito, Shoou-I Yu, Stuart Anderson, Michael Zollhöfer, Te-Li Wang, Shaojie Bai, Chenghui Li, Shih-En Wei, Rohan Joshi, Wyatt Borsos, Tomas Simon, Jason M. Saragih, Paul Theodosis, Alexander Greene, Anjani Josyula, Silvio Maeta, Andrew Jewett, Simion Venshtain, Christopher Heilman, Yueh-Tung Chen, Sidi Fu, Mohamed Elshaer, Tingfang Du, Longhua Wu, Shen-Chi Chen, Kai Kang, Michael Wu, Youssef Emad, Steven Longay, Ashley Brewer, Hitesh Shah, James Booth, Taylor Koska, Kayla Haidle, Matthew Andromalos, Joanna Hsu, Thomas Dauer, Peter Selednik, Timothy Godisart, Scott Ardisson, Matthew Cipperly, Ben Humberston, Lon Farr, Bob Hansen, Peihong Guo, Dave Braun, Steven Krenn, He Wen, Lucas Evans, Natalia Fadeeva, Matthew Stewart, Gabriel Schwartz, Divam Gupta, Gyeongsik Moon, Kaiwen Guo, Yuan Dong, Yichen Xu, Takaaki Shiratori, Fabian Prada, Bernardo Pires, Bo Peng, Julia Buffalini, Autumn Trimble, Kevyn McPhail, Melissa Schoeller, Yaser Sheikh:
Codec Avatar Studio: Paired Human Captures for Complete, Driveable, and Generalizable Avatars. - Huiping Zhuang, Yizhu Chen, Di Fang, Run He, Kai Tong, Hongxin Wei, Ziqian Zeng, Cen Chen:
GACL: Exemplar-Free Generalized Analytic Continual Learning. - Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Emad Barsoum:
QT-ViT: Improving Linear Attention in ViT with Quadratic Taylor Expansion. - Jaemyung Yu, Jaehyun Choi, Dong-Jae Lee, Hyeong Gwon Hong, Junmo Kim:
Self-supervised Transformation Learning for Equivariant Representations. - Adam Karvonen, Benjamin Wright, Can Rager, Rico Angell, Jannik Brinkmann, Logan Smith, Claudio Mayrink Verdun, David Bau, Samuel Marks:
Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models. - Francesco Cagnetta, Matthieu Wyart:
Towards a theory of how the structure of language is acquired by deep neural networks. - Yuhan Li, Hao Zhou, Wenxiang Shang, Ran Lin, Xuanhong Chen, Bingbing Ni:
AnyFit: Controllable Virtual Try-on for Any Combination of Attire Across Any Scenario. - Alexandre Galashov, Michalis K. Titsias, András György, Clare Lyle, Razvan Pascanu, Yee Whye Teh, Maneesh Sahani:
Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset. - Yi Zeng, Xuelin Yang, Li Chen, Cristian Canton Ferrer, Ming Jin, Michael I. Jordan, Ruoxi Jia:
Fairness-Aware Meta-Learning via Nash Bargaining. - Volodymyr Tkachuk, Gellért Weisz, Csaba Szepesvári:
Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear qπ-Realizability and Concentrability. - Jingzhe Shi, Qinwei Ma, Huan Ma, Lei Li:
Scaling Law for Time Series Forecasting. - Andy Zou, Long Phan, Justin Wang, Derek Duenas, Maxwell Lin, Maksym Andriushchenko, J. Zico Kolter, Matt Fredrikson, Dan Hendrycks:
Improving Alignment and Robustness with Circuit Breakers. - Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, Nicholas Carlini:
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models. - Pasan Dissanayake, Sanghamitra Dutta:
Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory. - Benjamin Feuer, Robin Schirrmeister, Valeriia Cherepanova, Chinmay Hegde, Frank Hutter, Micah Goldblum, Niv Cohen, Colin White:
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks. - Yu Yang, Siddhartha Mishra, Jeffrey N. Chiang, Baharan Mirzasoleiman:
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models. - Stefanos Pertigkiozoglou, Evangelos Chatzipantazis, Shubhendu Trivedi, Kostas Daniilidis:
Improving Equivariant Model Training via Constraint Relaxation. - Wei Pang, Masoumeh Shafieinejad, Lucy Liu, Stephanie Hazlewood, Xi He:
ClavaDDPM: Multi-relational Data Synthesis with Cluster-guided Diffusion Models. - Sahar Abdelnabi, Amr Gomaa, Sarath Sivaprasad, Lea Schönherr, Mario Fritz:
Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation. - Albert Q. Jiang, Wenda Li, Mateja Jamnik:
Multi-language Diversity Benefits Autoformalization. - Nadav Merlis, Dorian Baudry, Vianney Perchet:
The Value of Reward Lookahead in Reinforcement Learning. - Yunjuan Wang, Raman Arora:
On the Stability and Generalization of Meta-Learning. - Jiayi Wu, Hao Sun, Hengyi Cai, Lixin Su, Shuaiqiang Wang, Dawei Yin, Xiang Li, Ming Gao:
Cross-model Control: Improving Multiple Large Language Models in One-time Training. - Zeyu Jia, Jian Qian, Alexander Rakhlin, Chen-Yu Wei:
How Does Variance Shape the Regret in Contextual Bandits? - Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann:
Understanding and Minimising Outlier Features in Transformer Training. - Taeyoung Yun, Sujin Yun, Jaewoo Lee, Jinkyoo Park:
Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization. - Timothy Nest, Maxence Ernoult:
Towards training digitally-tied analog blocks via hybrid gradient computation. - Julia Kostin, Nicola Gnecco, Fanny Yang:
Achievable distributional robustness when the robust risk is only partially identified. - Fu-Yun Wang, Zhaoyang Huang, Alexander William Bergman, Dazhong Shen, Peng Gao, Michael Lingelbach, Keqiang Sun, Weikang Bian, Guanglu Song, Yu Liu, Xiaogang Wang, Hongsheng Li:
Phased Consistency Models. - Xi Chen, Yutong Feng, Mengting Chen, Yiyang Wang, Shilong Zhang, Yu Liu, Yujun Shen, Hengshuang Zhao:
Zero-shot Image Editing with Reference Imitation. - Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Shruti Bhosale, Hsien-Hsin S. Lee, Carole-Jean Wu, Benjamin Lee:
Toward Efficient Inference for Mixture of Experts. - Ziyu Shan, Yujie Zhang, Yipeng Liu, Yiling Xu:
Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization. - Julius Kunze, Daniel Severo, Jan-Willem van de Meent, James Townsend:
Practical Shuffle Coding. - Jiahao Lu, Jiacheng Deng, Ruijie Zhu, Yanzhe Liang, Wenfei Yang, Xu Zhou, Tianzhu Zhang:
DN-4DGS: Denoised Deformable Network with Temporal-Spatial Aggregation for Dynamic Scene Rendering. - Yuxin Jia, Youfang Lin, Jing Yu, Shuo Wang, Tianhao Liu, Huaiyu Wan:
PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting. - Yu Zhang, Ruoyu Li, Nengwu Wu, Qing Li, Xinhan Lin, Yang Hu, Tao Li, Yong Jiang:
Dissect Black Box: Interpreting for Rule-Based Explanations in Unsupervised Anomaly Detection. - Sy-Tuyen Ho, Tuan Van Vo, Somayeh Ebrahimkhani, Ngai-Man Cheung:
Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights. - Futoshi Futami, Masahiro Fujisawa:
Information-theoretic Generalization Analysis for Expected Calibration Error. - Usha Bhalla, Alex Oesterling, Suraj Srinivas, Flávio P. Calmon, Himabindu Lakkaraju:
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE). - Rémi Bardenet, Subhroshekhar Ghosh, Hugo Simon-Onfroy, Hoang Son Tran:
Small coresets via negative dependence: DPPs, linear statistics, and concentration. - Xinmeng Huang, Shuo Li, Edgar Dobriban, Osbert Bastani, Hamed Hassani, Dongsheng Ding:
One-Shot Safety Alignment for Large Language Models via Optimal Dualization. - Drago Plecko, Elias Bareinboim:
Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making. - Lisa Bedin, Gabriel Cardoso, Josselin Duchateau, Rémi Dubois, Eric Moulines:
Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals. - Xiaobao Wu, Thong Nguyen, Delvin Zhang, William Yang Wang, Anh Tuan Luu:
FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Model. - Dong Huang, Jianbo Dai, Han Weng, Puzhen Wu, Yuhao Qing, Heming Cui, Zhijiang Guo, Jie Zhang:
EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization. - Abdurakhmon Sadiev, Grigory Malinovsky, Eduard Gorbunov, Igor Sokolov, Ahmed Khaled, Konstantin Burlachenko, Peter Richtárik:
Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences. - Nina Gubina, Andrei Dmitrenko, Gleb V. Solovev, Lyubov Yamshchikova, Oleg Petrov, Ivan Lebedev, Nikita Serov, Grigorii Kirgizov, Nikolay O. Nikitin, Vladimir Vinogradov:
Hybrid Generative AI for De Novo Design of Co-Crystals with Enhanced Tabletability. - Jingen Qu, Yufei Chen, Xiaodong Yue, Wei Fu, Qiguang Huang:
Hyper-opinion Evidential Deep Learning for Out-of-Distribution Detection. - The Viet Bui, Tien Mai, Thanh Hong Nguyen:
Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games. - Core Francisco Park, Maya Okawa, Andrew Lee, Ekdeep Singh Lubana, Hidenori Tanaka:
Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space. - Nikhil Khandekar, Qiao Jin, Guangzhi Xiong, Soren Dunn, Serina S. Applebaum, Zain Anwar, Maame Sarfo-Gyamfi, Conrad W. Safranek, Abid A Anwar, Andrew Zhang, Aidan Gilson, Maxwell B. Singer, Amisha D. Dave, Andrew Taylor, Aidong Zhang, Qingyu Chen, Zhiyong Lu:
MedCalc-Bench: Evaluating Large Language Models for Medical Calculations. - Guodong Du, Junlin Lee, Jing Li, Runhua Jiang, Yifei Guo, Shuyang Yu, Hanting Liu, Sim Kuan Goh, Ho-Kin Tang, Daojing He, Min Zhang:
Parameter Competition Balancing for Model Merging. - Yanlin Qu, Jose H. Blanchet, Peter W. Glynn:
Deep Learning for Computing Convergence Rates of Markov Chains. - Cheng Li, Mengzhuo Chen, Jindong Wang, Sunayana Sitaram, Xing Xie:
CultureLLM: Incorporating Cultural Differences into Large Language Models. - Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng, Liwei Wang:
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction. - Qihang Zhou, Jiangtao Yan, Shibo He, Wenchao Meng, Jiming Chen:
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection. - Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang:
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models. - Yifei Li, Yuchen Sun, Pingchuan Ma, Eftychios Sifakis, Tao Du, Bo Zhu, Wojciech Matusik:
NeuralFluid: Nueral Fluidic System Design and Control with Differentiable Simulation. - Muthu Chidambaram, Khashayar Gatmiry, Sitan Chen, Holden Lee, Jianfeng Lu:
What does guidance do? A fine-grained analysis in a simple setting. - Sonia Laguna, Ricards Marcinkevics, Moritz Vandenhirtz, Julia E. Vogt:
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? - Ziyang Chen, Daniel Geng, Andrew Owens:
Images that Sound: Composing Images and Sounds on a Single Canvas. - Jonas Belouadi, Simone Paolo Ponzetto, Steffen Eger:
DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ. - Aozhong Zhang, Naigang Wang, Yanxia Deng, Xin Li, Zi Yang, Penghang Yin:
MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization. - Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen T. Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia:
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models. - Zeyu Wang, Xiyuxing Zhang, Ruotong Yu, Yuntao Wang, Kenneth Christofferson, Jingru Zhang, Alex Mariakakis, Yuanchun Shi:
DreamCatcher: A Wearer-aware Multi-modal Sleep Event Dataset Based on Earables in Non-restrictive Environments. - Dennis Grinwald, Philipp Wiesner, Shinichi Nakajima:
Federated Learning over Connected Modes. - Senmao Li, Taihang Hu, Joost van de Weijer, Fahad Shahbaz Khan, Tao Liu, Linxuan Li, Shiqi Yang, Yaxing Wang, Ming-Ming Cheng, Jian Yang:
Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference. - Yuri Kinoshita, Taro Toyoizumi:
A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness. - Yanping Li, Jingshen Wang, Waverly Wei:
Dynamic Subgroup Identification in Covariate-adjusted Response-adaptive Randomization Experiments. - Huanan Li, Juntao Guan, Lai Rui, Sijun Ma, Lin Gu, Noperson:
TinyLUT: Tiny Look-Up Table for Efficient Image Restoration at the Edge. - Julian Zimmert, Teodor Vanislavov Marinov:
PRODuctive bandits: Importance Weighting No More. - Ruiqi Liu, Boyu Diao, Libo Huang, Zijia An, Zhulin An, Yongjun Xu:
Continual Learning in the Frequency Domain. - Kunyu Peng, Di Wen, Kailun Yang, Ao Luo, Yufan Chen, Jia Fu, M. Saquib Sarfraz, Alina Roitberg, Rainer Stiefelhagen:
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler. - Abhiram Iyer, Sarthak Chandra, Sugandha Sharma, Ila Fiete:
Flexible mapping of abstract domains by grid cells via self-supervised extraction and projection of generalized velocity signals. - Yarin Bar, Shalev Shaer, Yaniv Romano:
Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approach. - Negin Musavi, Ziyao Guo, Geir E. Dullerud, Yingying Li:
Identification of Analytic Nonlinear Dynamical Systems with Non-asymptotic Guarantees. - Yixiong Zou, Shuai Yi, Yuhua Li, Ruixuan Li:
A Closer Look at the CLS Token for Cross-Domain Few-Shot Learning. - Hung Le, Doyen Sahoo, Yingbo Zhou, Caiming Xiong, Silvio Savarese:
INDICT: Code Generation with Internal Dialogues of Critiques for Both Security and Helpfulness. - Junfan Li, Zheshun Wu, Zenglin Xu, Irwin King:
On the Necessity of Collaboration for Online Model Selection with Decentralized Data. - Michael Saxon, Fatima Jahara, Mahsa Khoshnoodi, Yujie Lu, Aditya Sharma, William Yang Wang:
Who Evaluates the Evaluations? Objectively Scoring Text-to-Image Prompt Coherence Metrics with T2IScoreScore (TS2). - Hongming Zhang, Chenjun Xiao, Chao Gao, Han Wang, Bo Xu, Martin Müller:
Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration. - Jiayu Liu, Zhenya Huang, Tong Xiao, Jing Sha, Jinze Wu, Qi Liu, Shijin Wang, Enhong Chen:
SocraticLM: Exploring Socratic Personalized Teaching with Large Language Models. - Wenjun Zhang, Liangxiao Jiang, Chaoqun Li:
IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing. - Yan Sun, Li Shen, Dacheng Tao:
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs. - Riccardo Poiani, Gabriele Curti, Alberto Maria Metelli, Marcello Restelli:
Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning. - Jinsong Chen, Hanpeng Liu, John E. Hopcroft, Kun He:
Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers. - Binqian Xu, Xiangbo Shu, Haiyang Mei, Zechen Bai, Basura Fernando, Mike Zheng Shou, Jinhui Tang:
DoFIT: Domain-aware Federated Instruction Tuning with Alleviated Catastrophic Forgetting. - Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi:
In-Context Learning with Representations: Contextual Generalization of Trained Transformers. - Jiehua Chen, Christian Hatschka, Sofia Simola:
Multi-Winner Reconfiguration. - Sanyam Kapoor, Nate Gruver, Manley Roberts, Katie Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson:
Large Language Models Must Be Taught to Know What They Don't Know. - Gyeonghoon Ko, Hyunsu Kim, Juho Lee:
Learning Infinitesimal Generators of Continuous Symmetries from Data. - Xindi Wu, Dingli Yu, Yangsibo Huang, Olga Russakovsky, Sanjeev Arora:
ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty. - Zijian Dong, Ruilin Li, Yilei Wu, Thuan Tinh Nguyen, Joanna Su Xian Chong, Fang Ji, Nathanael Ren Jie Tong, Christopher Chen, Juan Helen Zhou:
Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking. - Jianan Li, Quan Tu, Cunli Mao, Zhengtao Yu, Ji-Rong Wen, Rui Yan:
StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses. - Rory Young, Nicolas Pugeault:
Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach. - Yachao Liang, Min Yu, Gang Li, Jianguo Jiang, Boquan Li, Feng Yu, Ning Zhang, Xiang Meng, Weiqing Huang:
SpeechForensics: Audio-Visual Speech Representation Learning for Face Forgery Detection. - Leena Chennuru Vankadara, Jin Xu, Moritz Haas, Volkan Cevher:
On Feature Learning in Structured State Space Models. - Shiang Qi, Yakun Yu, Russell Greiner:
Toward Conditional Distribution Calibration in Survival Prediction. - Ziyi Chen, Xiaocong Yang, Jiacheng Lin, Chenkai Sun, Kevin Chen-Chuan Chang, Jie Huang:
Cascade Speculative Drafting for Even Faster LLM Inference. - Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Hyeji Kim, Michael Gastpar, Chanakya Ekbote:
Local to Global: Learning Dynamics and Effect of Initialization for Transformers. - Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low:
Localized Zeroth-Order Prompt Optimization. - Juliusz Ziomek, Masaki Adachi, Michael A. Osborne:
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal. - Mirco Giacobbe, Daniel Kroening, Abhinandan Pal, Michael Tautschnig:
Neural Model Checking. - Miaosen Zhang, Yixuan Wei, Zhen Xing, Yifei Ma, Zuxuan Wu, Ji Li, Zheng Zhang, Qi Dai, Chong Luo, Xin Geng, Baining Guo:
Aligning Vision Models with Human Aesthetics in Retrieval: Benchmarks and Algorithms. - Rachel Longjohn, Markelle Kelly, Sameer Singh, Padhraic Smyth:
Benchmark Data Repositories for Better Benchmarking. - Hyunsuk Kim, Liam Hodgkinson, Ryan Theisen, Michael W. Mahoney:
How many classifiers do we need? - Khoa Vo, Thinh Phan, Kashu Yamazaki, Minh Tran, Ngan Le:
HENASY: Learning to Assemble Scene-Entities for Interpretable Egocentric Video-Language Model. - Minsu Kim, Walid Saad, Mérouane Debbah, Choong Seon Hong:
SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead. - Chris Lu, Samuel Holt, Claudio Fanconi, Alex J. Chan, Jakob N. Foerster, Mihaela van der Schaar, Robert T. Lange:
Discovering Preference Optimization Algorithms with and for Large Language Models. - Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer:
Interventional Causal Discovery in a Mixture of DAGs. - Zhishuai Liu, Pan Xu:
Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning. - Junlin Xie, Ruifei Zhang, Zhihong Chen, Xiang Wan, Guanbin Li:
WhodunitBench: Evaluating Large Multimodal Agents via Murder Mystery Games. - Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias B. Khalil:
Neur2BiLO: Neural Bilevel Optimization. - Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang:
Proving Theorems Recursively. - Chaitanya Goswami, Amanda Merkley:
Analytically deriving Partial Information Decomposition for affine systems of stable and convolution-closed distributions. - Nikolaos-Antonios Ypsilantis, Kaifeng Chen, André Araújo, Ondrej Chum:
UDON: Universal Dynamic Online distillatioN for generic image representations. - Tongxin Li, Hao Liu, Yisong Yue:
Disentangling Linear Quadratic Control with Untrusted ML Predictions. - Zibin Dong, Yifu Yuan, Jianye Hao, Fei Ni, Yi Ma, Pengyi Li, Yan Zheng:
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making. - William Brandon, Mayank Mishra, Aniruddha Nrusimha, Rameswar Panda, Jonathan Ragan-Kelley:
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention. - Fan Yao, Yiming Liao, Jingzhou Liu, Shaoliang Nie, Qifan Wang, Haifeng Xu, Hongning Wang:
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms. - Edwin Zhang, Vincent Zhu, Naomi Saphra, Anat Kleiman, Benjamin L. Edelman, Milind Tambe, Sham M. Kakade, Eran Malach:
Transcendence: Generative Models Can Outperform The Experts That Train Them. - Yizuo Chen, Adnan Darwiche:
Identifying Causal Effects Under Functional Dependencies. - Yuwu Lu, Haoyu Huang, Xue Hu:
Style Adaptation and Uncertainty Estimation for Multi-Source Blended-Target Domain Adaptation. - Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky:
Linear Regression using Heterogeneous Data Batches. - Jeonghye Kim, Suyoung Lee, Woojun Kim, Youngchul Sung:
Adaptive Q-Aid for Conditional Supervised Learning in Offline Reinforcement Learning. - Mingbo Hong, Shen Cheng, Haibin Huang, Haoqiang Fan, Shuaicheng Liu:
You Only Look Around: Learning Illumination-Invariant Feature for Low-light Object Detection. - Dongsu Song, Daehwa Ko, Jay Hoon Jung:
Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object Detection. - Andy Lo, Albert Q. Jiang, Wenda Li, Mateja Jamnik:
End-to-End Ontology Learning with Large Language Models. - Yanfang Ling, Jiyong Li, Lingbo Li, Shangsong Liang:
Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing. - Xiangxin Zhou, Jiaqi Guan, Yijia Zhang, Xingang Peng, Liang Wang, Jianzhu Ma:
Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design. - Xingru Huang, Yihao Guo, Jian Huang, Tianyun Zhang, Hong He, Shaowei Jiang, Yaoqi Sun:
Upping the Game: How 2D U-Net Skip Connections Flip 3D Segmentation. - Peter Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Adithya Iyer, Sai Charitha Akula, Shusheng Yang, Jihan Yang, Manoj Middepogu, Ziteng Wang, Xichen Pan, Rob Fergus, Yann LeCun, Saining Xie:
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs. - Bahri Batuhan Bilecen, Ahmet Berke Gökmen, Aysegul Dundar:
Dual Encoder GAN Inversion for High-Fidelity 3D Head Reconstruction from Single Images. - Mingyu Xu, Xin Men, Bingning Wang, Qingyu Zhang, Hongyu Lin, Xianpei Han, Weipeng Chen:
Base of RoPE Bounds Context Length. - Xin Lu, Yanyan Zhao, Bing Qin, Liangyu Huo, Qing Yang, Dongliang Xu:
How does Architecture Influence the Base Capabilities of Pre-trained Language Models? A Case Study Based on FFN-Wider and MoE Transformers. - Fan-Yun Sun, S. I. Harini, Angela Yi, Yihan Zhou, Alex Zook, Jonathan Tremblay, Logan Cross, Jiajun Wu, Nick Haber:
FactorSim: Generative Simulation via Factorized Representation. - Jake Grigsby, Justin Sasek, Samyak Parajuli, Daniel Adebi, Amy Zhang, Yuke Zhu:
AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers. - Suyuan Liu, Siwei Wang, Ke Liang, Junpu Zhang, Zhibin Dong, Tianrui Liu, En Zhu, Xinwang Liu, Kunlun He:
Alleviate Anchor-Shift: Explore Blind Spots with Cross-View Reconstruction for Incomplete Multi-View Clustering. - Ge Yang, Changyi He, Jinyang Guo, Jianyu Wu, Yifu Ding, Aishan Liu, Haotong Qin, Pengliang Ji, Xianglong Liu:
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment. - Song Xia, Wenhan Yang, Yi Yu, Xun Lin, Henghui Ding, Lingyu Duan, Xudong Jiang:
Transferable Adversarial Attacks on SAM and Its Downstream Models. - Yanrui Du, Sendong Zhao, Danyang Zhao, Ming Ma, Yuhan Chen, Liangyu Huo, Qing Yang, Dongliang Xu, Bing Qin:
MoGU: A Framework for Enhancing Safety of LLMs While Preserving Their Usability. - Kangrui Ruan, Junzhe Zhang, Xuan Di, Elias Bareinboim:
Causal Imitation for Markov Decision Processes: a Partial Identification Approach. - Xian Wu, Yutian Zhao, Yunyan Zhang, Jiageng Wu, Zhihong Zhu, Yingying Zhang, Yi Ouyang, Ziheng Zhang, Huimin Wang, Zhenxi Lin, Jie Yang, Shuang Zhao, Yefeng Zheng:
MedJourney: Benchmark and Evaluation of Large Language Models over Patient Clinical Journey. - François Rozet, Gérôme Andry, François Lanusse, Gilles Louppe:
Learning Diffusion Priors from Observations by Expectation Maximization. - Yiwei Li, Jiayi Shi, Shaoxiong Feng, Peiwen Yuan, Xinglin Wang, Boyuan Pan, Heda Wang, Yao Hu, Kan Li:
Instruction Embedding: Latent Representations of Instructions Towards Task Identification. - Jiachang Liu, Rui Zhang, Cynthia Rudin:
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models. - Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei:
DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs. - Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev:
DAGER: Exact Gradient Inversion for Large Language Models. - Kyung Jin Seo, Junghoon Seo, Hanseok Jeong, Sangpil Kim, Sang Ho Yoon:
Posture-Informed Muscular Force Learning for Robust Hand Pressure Estimation. - Hugo Laurençon, Léo Tronchon, Matthieu Cord, Victor Sanh:
What matters when building vision-language models? - Huao Li, Hossein Nourkhiz Mahjoub, Behdad Chalaki, Vaishnav Tadiparthi, Kwonjoon Lee, Ehsan Moradi-Pari, Charles Lewis, Katia P. Sycara:
Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication. - Ruiqi Li, Yiu-ming Cheung:
Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting. - Shuai Wang, Zexian Li, Tianhui Song, Xubin Li, Tiezheng Ge, Bo Zheng, Limin Wang:
Exploring DCN-like architecture for fast image generation with arbitrary resolution. - Chaoxi Niu, Guansong Pang, Ling Chen, Bing Liu:
Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach. - Donghao Luo, Xue Wang:
DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching. - Shengbo Wang, Jose H. Blanchet, Peter W. Glynn:
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations. - Song Wang, Zihan Chen, Chengshuai Shi, Cong Shen, Jundong Li:
Mixture of Demonstrations for In-Context Learning. - Dan Qiao, Yu-Xiang Wang:
Differentially Private Reinforcement Learning with Self-Play. - Zhaohua Chen, Rui Ai, Mingwei Yang, Yuqi Pan, Chang Wang, Xiaotie Deng:
Contextual Decision-Making with Knapsacks Beyond the Worst Case. - Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmir Mutny:
Transition Constrained Bayesian Optimization via Markov Decision Processes. - Dominik Hintersdorf, Lukas Struppek, Kristian Kersting, Adam Dziedzic, Franziska Boenisch:
Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models. - Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu:
Model-Based Transfer Learning for Contextual Reinforcement Learning. - Xun Guo, Yongxin He, Shan Zhang, Ting Zhang, Wanquan Feng, Haibin Huang, Chongyang Ma:
DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning. - Lei Wang, Jieming Bian, Letian Zhang, Chen Chen, Jie Xu:
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains. - Zhiyuan Fan, Christian Kroer, Gabriele Farina:
On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games. - Haiwen Huang, Songyou Peng, Dan Zhang, Andreas Geiger:
Renovating Names in Open-Vocabulary Segmentation Benchmarks. - Yehe Liu, Alexander Krull, Hector Basevi, Ales Leonardis, Michael W. Jenkins:
bit2bit: 1-bit quanta video reconstruction via self-supervised photon prediction. - ZhenTing Liu, ShangTse Chen:
Trap-MID: Trapdoor-based Defense against Model Inversion Attacks. - Arshia Hemmat, Adam Davies, Tom A. Lamb, Jianhao Yuan, Philip Torr, Ashkan Khakzar, Francesco Pinto:
Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models. - Fan Lin, Shuyi Xie, Yong Dai, Wenlin Yao, Tianjiao Lang, Yu Zhang:
IDGen: Item Discrimination Induced Prompt Generation for LLM Evaluation. - Bozhen Hu, Cheng Tan, Yongjie Xu, Zhangyang Gao, Jun Xia, Lirong Wu, Stan Z. Li:
ProtGO: Function-Guided Protein Modeling for Unified Representation Learning. - Ilias Diakonikolas, Nikos Zarifis:
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise. - Sithursan Sivasubramaniam, Cedric Osei-Akoto, Yi Zhang, Kurt Stockinger, Jonathan Fürst:
SM3-Text-to-Query: Synthetic Multi-Model Medical Text-to-Query Benchmark. - Scott Cheng, Mahmut T. Kandemir, Ding-Yong Hong:
Speculative Monte-Carlo Tree Search. - Qi Ma, Danda Pani Paudel, Ender Konukoglu, Luc Van Gool:
Implicit Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes. - Keran Chen, Joon Suk Huh, Kirthevasan Kandasamy:
Learning to Price Homogeneous Data. - Yilan Chen, Wei Huang, Lily Weng:
Provable and Efficient Dataset Distillation for Kernel Ridge Regression. - Julius Vetter, Guy Moss, Cornelius Schröder, Richard Gao, Jakob H. Macke:
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation. - Kaja Gruntkowska, Alexander Tyurin, Peter Richtárik:
Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity. - Zhao Song, Ali Vakilian, David P. Woodruff, Samson Zhou:
On Socially Fair Low-Rank Approximation and Column Subset Selection. - Zhihua Wen, Zhiliang Tian, Zexin Jian, Zhen Huang, Pei Ke, Yifu Gao, Minlie Huang, Dongsheng Li:
Perception of Knowledge Boundary for Large Language Models through Semi-open-ended Question Answering. - Aristeidis Panos:
Decomposable Transformer Point Processes. - Fang Dong, Mengyi Chen, Jixian Zhou, Yubin Shi, Yixuan Chen, Mingzhi Dong, Yujiang Wang, Dongsheng Li, Xiaochen Yang, Rui Zhu, Robert P. Dick, Qin Lv, Fan Yang, Tun Lu, Ning Gu, Li Shang:
Once Read is Enough: Domain-specific Pretraining-free Language Models with Cluster-guided Sparse Experts for Long-tail Domain Knowledge. - Rajarshi Saha, Naomi Sagan, Varun Srivastava, Andrea Goldsmith, Mert Pilanci:
Compressing Large Language Models using Low Rank and Low Precision Decomposition. - Sainyam Galhotra, Joseph Y. Halpern:
Intervention and Conditioning in Causal Bayesian Networks. - Gonçalo Rui Alves Faria, Sweta Agrawal, António Farinhas, Ricardo Rei, José Guilherme Camargo de Souza, André F. T. Martins:
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation. - Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou, Sheng Zhong, Nanning Zheng, Ying Nian Wu:
Molecule Design by Latent Prompt Transformer. - Xinyu Fang, Kangrui Mao, Haodong Duan, Xiangyu Zhao, Yining Li, Dahua Lin, Kai Chen:
MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding. - Shiji Zhao, Ranjie Duan, Xizhe Wang, Xingxing Wei:
Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation. - Lucine L. Oganesian, Omid G. Sani, Maryam Shanechi:
Spectral Learning of Shared Dynamics Between Generalized-Linear Processes. - Umangi Jain, Ashkan Mirzaei, Igor Gilitschenski:
GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting. - Yuli Slavutsky, Yuval Benjamini:
Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations. - Spandan Madan, Will Xiao, Mingran Cao, Hanspeter Pfister, Margaret S. Livingstone, Gabriel Kreiman:
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex. - Leyla Biabani, Annika Hennes, Denise La Gordt Dillie, Morteza Monemizadeh, Melanie Schmidt:
Improved Guarantees for Fully Dynamic k-Center Clustering with Outliers in General Metric Spaces. - Jacob K. Christopher, Stephen Baek, Ferdinando Fioretto:
Constrained Synthesis with Projected Diffusion Models. - Yeonsu Kwon, Jiho Kim, Gyubok Lee, Seongsu Bae, Daeun Kyung, Wonchul Cha, Tom Pollard, Alistair Johnson, Edward Choi:
EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records. - Tianlu Zhang, Kurt Debattista, Qiang Zhang, Guiguang Ding, Jungong Han:
Revisiting motion information for RGB-Event tracking with MOT philosophy. - Yijia Shao, Tianshi Li, Weiyan Shi, Yanchen Liu, Diyi Yang:
PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action. - Meihan Liu, Zhen Zhang, Jiachen Tang, Jiajun Bu, Bingsheng He, Sheng Zhou:
Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation. - Raymond Zhang, Richard Combes:
Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox. - Minkyu Jeon, Rishwanth Raghu, Miro Astore, Geoffrey Woollard, Ryan Feathers, Alkin Kaz, Sonya M. Hanson, Pilar Cossio, Ellen D. Zhong:
CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM. - Jiaqi Lv, Yangfan Liu, Shiyu Xia, Ning Xu, Miao Xu, Gang Niu, Min-Ling Zhang, Masashi Sugiyama, Xin Geng:
What Makes Partial-Label Learning Algorithms Effective? - Kaibo Wang, Xiaowen Fu, Yuxuan Han, Yang Xiang:
DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification. - Yannan Chen, Beichen Huang, Licheng Zhao, Kaiming Shen:
Multidimensional Fractional Programming for Normalized Cuts. - Bowen Song, Jason Hu, Zhaoxu Luo, Jeffrey A. Fessler, Liyue Shen:
DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction. - Nikita Gushchin, Daniil Selikhanovych, Sergei Kholkin, Evgeny Burnaev, Alexander Korotin:
Adversarial Schrödinger Bridge Matching. - Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao:
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models. - Chenyang Le, Yao Qian, Dongmei Wang, Long Zhou, Shujie Liu, Xiaofei Wang, Midia Yousefi, Yanmin Qian, Jinyu Li, Michael Zeng:
TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation. - Yejin Choi, Jiwan Chung, Sumin Shim, Giyeong Oh, Youngjae Yu:
Towards Visual Text Design Transfer Across Languages. - Yunlu Chen, Francisco Vicente Carrasco, Christian Häne, Giljoo Nam, Jean-Charles Bazin, Fernando De la Torre:
Doubly Hierarchical Geometric Representations for Strand-based Human Hairstyle Generation. - Mengyu Zhao, Xi Chen, Xin Yuan, Shirin Jalali:
Untrained Neural Nets for Snapshot Compressive Imaging: Theory and Algorithms. - Chau Pham, Bryan A. Plummer:
Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers. - Xingming Long, Jie Zhang, Shiguang Shan, Xilin Chen:
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox. - Jihwan Kim, Junoh Kang, Jinyoung Choi, Bohyung Han:
FIFO-Diffusion: Generating Infinite Videos from Text without Training. - Yifei Wang, Yuyang Wu, Zeming Wei, Stefanie Jegelka, Yisen Wang:
A Theoretical Understanding of Self-Correction through In-context Alignment. - Dayoung Gong, Suha Kwak, Minsu Cho:
ActFusion: a Unified Diffusion Model for Action Segmentation and Anticipation. - Liyun Zhu, Lei Wang, Arjun Raj, Tom Gedeon, Chen Chen:
Advancing Video Anomaly Detection: A Concise Review and a New Dataset. - Hongyuan Tao, Hang Yu, Jianguo Li:
DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation. - Chuyang Zhao, Yuxin Song, Junru Chen, Kang Rong, Haocheng Feng, Gang Zhang, Shufan Ji, Jingdong Wang, Errui Ding, Yifan Sun:
Octopus: A Multi-modal LLM with Parallel Recognition and Sequential Understanding. - Dogyun Park, Sojin Lee, Sihyeon Kim, Taehoon Lee, Youngjoon Hong, Hyunwoo J. Kim:
Constant Acceleration Flow. - Vitaly Feldman, Audra McMillan, Satchit Sivakumar, Kunal Talwar:
Instance-Optimal Private Density Estimation in the Wasserstein Distance. - Subhojyoti Mukherjee, Anusha Lalitha, Kousha Kalantari, Aniket Deshmukh, Ge Liu, Yifei Ma, Branislav Kveton:
Optimal Design for Human Preference Elicitation. - Zhiwei Li, Yiqiu LI, Binbin Lin, Zhongming Jin, Weizhong Zhang:
Low Precision Local Training is Enough for Federated Learning. - Yiheng Li, Heyang Jiang, Akio Kodaira, Masayoshi Tomizuka, Kurt Keutzer, Chenfeng Xu:
Immiscible Diffusion: Accelerating Diffusion Training with Noise Assignment. - Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo:
Continuous Product Graph Neural Networks. - Jinzhu Luo, Dingyang Chen, Qi Zhang:
Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control. - Wenshan Wu, Shaoguang Mao, Yadong Zhang, Yan Xia, Li Dong, Lei Cui, Furu Wei:
Mind's Eye of LLMs: Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models. - Haoran Que, Jiaheng Liu, Ge Zhang, Chenchen Zhang, Xingwei Qu, Yinghao Ma, Feiyu Duan, Zhiqi Bai, Jiakai Wang, Yuanxing Zhang, Xu Tan, Jie Fu, Jiamang Wang, Lin Qu, Wenbo Su, Bo Zheng:
D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models. - Trong-Thuan Nguyen, Pha A. Nguyen, Xin Li, Jackson David Cothren, Alper Yilmaz, Khoa Luu:
CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos. - Zeki Kazan, Jerome P. Reiter:
Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy. - Zanlin Ni, Yulin Wang, Renping Zhou, Yizeng Han, Jiayi Guo, Zhiyuan Liu, Yuan Yao, Gao Huang:
ENAT: Rethinking Spatial-temporal Interactions in Token-based Image Synthesis. - Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Aidin Niaparast, Sergei Vassilvitskii:
Binary Search with Distributional Predictions. - Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael I. Jordan, Jiantao Jiao, Yuandong Tian, Stuart J. Russell:
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. - Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron:
GRANOLA: Adaptive Normalization for Graph Neural Networks. - Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach:
The Intelligible and Effective Graph Neural Additive Network. - Xinyu Zhou, Jinglun Li, Lingyi Hong, Kaixun Jiang, Pinxue Guo, Weifeng Ge, Wenqiang Zhang:
DeTrack: In-model Latent Denoising Learning for Visual Object Tracking. - Irina Saparina, Mirella Lapata:
AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queries. - Xiang Yue, Tianyu Zheng, Ge Zhang, Wenhu Chen:
MAmmoTH2: Scaling Instructions from the Web. - Xueqing Wu, Rui Zheng, Jingzhen Sha, Te-Lin Wu, Hanyu Zhou, Mohan Tang, Kai-Wei Chang, Nanyun Peng, Haoran Huang:
DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation. - Yue Yang, Mona Gandhi, Yufei Wang, Yifan Wu, Michael S. Yao, Chris Callison-Burch, James C. Gee, Mark Yatskar:
A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis. - Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jorg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller:
Imitating Language via Scalable Inverse Reinforcement Learning. - Yingqing Guo, Hui Yuan, Yukang Yang, Minshuo Chen, Mengdi Wang:
Gradient Guidance for Diffusion Models: An Optimization Perspective. - Hongjie Chen, Jingqiu Ding, Yiding Hua, David Steurer:
Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust. - Ruichen Jiang, Michal Derezinski, Aryan Mokhtari:
Stochastic Newton Proximal Extragradient Method. - Jiaming Ji, Boyuan Chen, Hantao Lou, Donghai Hong, Borong Zhang, Xuehai Pan, Tianyi Qiu, Juntao Dai, Yaodong Yang:
Aligner: Efficient Alignment by Learning to Correct. - Ruofan Wu, Guanhua Fang, Mingyang Zhang, Qiying Pan, Tengfei Liu, Weiqiang Wang:
On provable privacy vulnerabilities of graph representations. - Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang, Yang Zhang, Jonathan Scarlett, Zhanxing Zhu, Kenji Kawaguchi:
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization. - Louis Chen, Roberto Szechtman, Matan Seri:
On the Adversarial Robustness of Benjamini Hochberg. - Gregory Dexter, Petros Drineas, Rajiv Khanna:
The Space Complexity of Approximating Logistic Loss. - Li Zhang, Yan Zhong, Jianan Wang, Zhe Min, RujingWang, Liu Liu:
Rethinking 3D Convolution in $\ell_p$-norm Space. - Pierre Glaser, Kevin Han Huang, Arthur Gretton:
Near-Optimality of Contrastive Divergence Algorithms. - James Urquhart Allingham, Bruno Mlodozeniec, Shreyas Padhy, Javier Antorán, David Krueger, Richard E. Turner, Eric T. Nalisnick, José Miguel Hernández-Lobato:
A Generative Model of Symmetry Transformations. - Weifeng Liu, Tianyi She, Jiawei Liu, Boheng Li, Dongyu Yao, Ziyou Liang, Run Wang:
Lips Are Lying: Spotting the Temporal Inconsistency between Audio and Visual in Lip-Syncing DeepFakes. - Dillon Z. Chen, Sylvie Thiébaux:
Graph Learning for Numeric Planning. - Guanlin Li, Kangjie Chen, Shudong Zhang, Jie Zhang, Tianwei Zhang:
ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users. - Aditya Sinha, Siqi Zeng, Makoto Yamada, Han Zhao:
Learning Structured Representations with Hyperbolic Embeddings. - Rulin Shao, Jacqueline He, Akari Asai, Weijia Shi, Tim Dettmers, Sewon Min, Luke Zettlemoyer, Pang Wei Koh:
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore. - Etai Littwin, Omid Saremi, Madhu Advani, Vimal Thilak, Preetum Nakkiran, Chen Huang, Joshua M. Susskind:
How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. - Qiaozhe Zhang, Ruijie Zhang, Jun Sun, Yingzhuang Liu:
How Sparse Can We Prune A Deep Network: A Fundamental Limit Perspective. - Viswanath Sivakumar, Jeffrey Seely, Alan Du, Sean R. Bittner, Adam Berenzweig, Anuoluwapo Bolarinwa, Alexandre Gramfort, Michael I. Mandel:
emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography. - Shuyi Lin, Haoyu He, Tianhao Wei, Kaidi Xu, Huan Zhang, Gagandeep Singh, Changliu Liu, Cheng Tan:
NN4SysBench: Characterizing Neural Network Verification for Computer Systems. - Jiasheng Zhang, Jialin Chen, Menglin Yang, Aosong Feng, Shuang Liang, Jie Shao, Rex Ying:
DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs. - Thao Nguyen, Matthew Wallingford, Sebastin Santy, Wei-Chiu Ma, Sewoong Oh, Ludwig Schmidt, Pang Wei W. Koh, Ranjay Krishna:
Multilingual Diversity Improves Vision-Language Representations. - Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary C. Lipton:
Post-Hoc Reversal: Are We Selecting Models Prematurely? - Yanxiao Liu, Wei-Ning Chen, Ayfer Özgür, Cheuk Ting Li:
Universal Exact Compression of Differentially Private Mechanisms. - Shangshang Yang, Mingyang Chen, Ziwen Wang, Xiaoshan Yu, Panpan Zhang, Haiping Ma, Xingyi Zhang:
DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis. - Shenyuan Gao, Jiazhi Yang, Li Chen, Kashyap Chitta, Yihang Qiu, Andreas Geiger, Jun Zhang, Hongyang Li:
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability. - Zihao Chen, Chi-Heng Lin, Ran Liu, Jingyun Xiao, Eva L. Dyer:
Your contrastive learning problem is secretly a distribution alignment problem. - Tianyue Ou, Frank F. Xu, Aman Madaan, Jiarui Liu, Robert Lo, Abishek Sridhar, Sudipta Sengupta, Dan Roth, Graham Neubig, Shuyan Zhou:
Synatra: Turning Indirect Knowledge into Direct Demonstrations for Digital Agents at Scale. - Siyan Wang, Bradford Levy:
BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text. - Xuechen Zhang, Zijian Huang, Ege Onur Taga, Carlee Joe-Wong, Samet Oymak, Jiasi Chen:
Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning. - Du Chen, Geoffrey A. Chua:
Noisy Dual Mirror Descent: A Near Optimal Algorithm for Jointly-DP Convex Resource Allocation. - Chang Deng, Kevin Bello, Pradeep Ravikumar, Bryon Aragam:
Markov Equivalence and Consistency in Differentiable Structure Learning. - Chengwei Ren, Yifan Feng, Weixiang Zhang, Xiao-Ping (Steven) Zhang, Yue Gao:
Multi-scale Consistency for Robust 3D Registration via Hierarchical Sinkhorn Tree. - Sejun Park, Kihun Hong, Ganguk Hwang:
A Kernel Perspective on Distillation-based Collaborative Learning. - Ziang Zhang, Zehan Wang, Luping Liu, Rongjie Huang, Xize Cheng, Zhenhui Ye, Wang Lin, Huadai Liu, Haifeng Huang, Yang Zhao, Tao Jin, Siqi Zheng, Zhou Zhao:
Extending Multi-modal Contrastive Representations. - Fang Kong, Zilong Wang, Shuai Li:
Improved Analysis for Bandit Learning in Matching Markets. - Mengting Xu, De Ma, Huajin Tang, Qian Zheng, Gang Pan:
FEEL-SNN: Robust Spiking Neural Networks with Frequency Encoding and Evolutionary Leak Factor. - Ziyuan Zhang, Han Qiu, Maosen Zhang, Jun Liu, Bin Chen, Tianwei Zhang, Hewu Li:
COSMIC: Compress Satellite Image Efficiently via Diffusion Compensation. - Subhodh Kotekal:
Variance estimation in compound decision theory under boundedness. - Yun Xing, Yiheng Li, Ivan Laptev, Shijian Lu:
Mitigating Object Hallucination via Concentric Causal Attention. - Yanbing Liu, Jianwei Qin, Yan Liu, Xi Yue, Xun Liu, Guoqing Wang, Tianyu Li, Fangwei Ye, Wei Li:
Physics-Constrained Comprehensive Optical Neural Networks. - Hanchao Liu, Yujiang Li, Tai-Jiang Mu, Shi-Min Hu:
Recovering Complete Actions for Cross-dataset Skeleton Action Recognition. - Zhuofan Wen, Shangtong Gui, Yang Feng:
Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration. - Youjing Yu, Rui Xia, Qingxi Ma, Máté Lengyel, Guillaume Hennequin:
Second-order forward-mode optimization of recurrent neural networks for neuroscience. - Wei Li, William E. Bishop, Alice Li, Christopher Rawles, Folawiyo Campbell-Ajala, Divya Tyamagundlu, Oriana Riva:
On the Effects of Data Scale on UI Control Agents. - Pouya M. Ghari, Yanning Shen:
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning. - Adam Sun, Tiange Xiang, Scott L. Delp, Li Fei-Fei, Ehsan Adeli:
OccFusion: Rendering Occluded Humans with Generative Diffusion Priors. - Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljacic:
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation. - Yunshi Wen, Tengfei Ma, Lily Weng, Lam M. Nguyen, Anak Agung Julius:
Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification. - Fabian Gröger, Simone Lionetti, Philippe Gottfrois, Álvaro González-Jiménez, Ludovic Amruthalingam, Matthew Groh, Alexander A. Navarini, Marc Pouly:
Intrinsic Self-Supervision for Data Quality Audits. - Bingqing Song, Boran Han, Shuai Zhang, Jie Ding, Mingyi Hong:
Unraveling the Gradient Descent Dynamics of Transformers. - Jaehyun Nam, Kyuyoung Kim, Seunghyuk Oh, Jihoon Tack, Jaehyung Kim, Jinwoo Shin:
Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning. - Chenhui Xu, Fuxun Yu, Maoliang Li, Zihao Zheng, Zirui Xu, Jinjun Xiong, Xiang Chen:
Infinite-Dimensional Feature Interaction. - Haozhe Chen, Ang Li, Ethan Che, Jing Dong, Tianyi Peng, Hongseok Namkoong:
QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers. - Jasper Dekoninck, Mark Niklas Müller, Martin T. Vechev:
ConStat: Performance-Based Contamination Detection in Large Language Models. - Dohyeong Kim, Taehyun Cho, Seungyub Han, Hojun Chung, Kyungjae Lee, Songhwai Oh:
Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees. - Deyu Zou, Shikun Liu, Siqi Miao, Victor Fung, Shiyu Chang, Pan Li:
GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts. - Rongyuan Wu, Lingchen Sun, Zhiyuan Ma, Lei Zhang:
One-Step Effective Diffusion Network for Real-World Image Super-Resolution. - Tieyuan Chen, Huabin Liu, Tianyao He, Yihang Chen, Chaofan Gan, Xiao Ma, Cheng Zhong, Yang Zhang, Yingxue Wang, Hui Lin, Weiyao Lin:
MECD: Unlocking Multi-Event Causal Discovery in Video Reasoning. - Haowei Zhu, Dehua Tang, Ji Liu, Mingjie Lu, Jintu Zheng, Jinzhang Peng, Dong Li, Yu Wang, Fan Jiang, Lu Tian, Spandan Tiwari, Ashish Sirasao, Jun-Hai Yong, Bin Wang, Emad Barsoum:
DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization. - Haochen Liu, Li Chen, Yu Qiao, Chen Lv, Hongyang Li:
Reasoning Multi-Agent Behavioral Topology for Interactive Autonomous Driving. - Liam Collins, Advait Parulekar, Aryan Mokhtari, Sujay Sanghavi, Sanjay Shakkottai:
In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness. - Hangchi Shen, Qian Zheng, Huamin Wang, Gang Pan:
Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks. - Zhou Lu:
When Is Inductive Inference Possible? - Bin Han, Yi-Xuan Sun, Ya-Lin Zhang, Libang Zhang, Haoran Hu, Longfei Li, Jun Zhou, Guo Ye, Huimei He:
Collaborative Refining for Learning from Inaccurate Labels. - Paritosh Parmar, Eric Peh, Ruirui Chen, Ting En Lam, Yuhan Chen, Elston Tan, Basura Fernando:
CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes. - Harin Lee, Min-hwan Oh:
Improved Regret of Linear Ensemble Sampling. - Fivos Kalogiannis, Jingming Yan, Ioannis Panageas:
Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem. - Yuchen Ren, Zhiyuan Chen, Lifeng Qiao, Hongtai Jing, Yuchen Cai, Sheng Xu, Peng Ye, Xinzhu Ma, Siqi Sun, Hongliang Yan, Dong Yuan, Wanli Ouyang, Xihui Liu:
BEACON: Benchmark for Comprehensive RNA Tasks and Language Models. - Rohan Gupta, Iván Arcuschin Moreno, Thomas Kwa, Adrià Garriga-Alonso:
InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques. - Tinashe Handina, Eric Mazumdar:
Understanding Model Selection for Learning in Strategic Environments. - Gowthami Somepalli, Arkabandhu Chowdhury, Jonas Geiping, Ronen Basri, Tom Goldstein, David Jacobs:
CALVIN: Improved Contextual Video Captioning via Instruction Tuning. - Huatian Zhang, Lei Zhang, Yongdong Zhang, Zhendong Mao:
Homology Consistency Constrained Efficient Tuning for Vision-Language Models. - Aniketh Janardhan Reddy, Xinyang Geng, Michael Herschl, Sathvik Kolli, Aviral Kumar, Patrick Hsu, Sergey Levine, Nilah Ioannidis:
Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization. - Yihan Zhang, Marco Mondelli:
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods. - Felix Teufel, Carsten Stahlhut, Jesper Ferkinghoff-Borg:
Batched Energy-Entropy acquisition for Bayesian Optimization. - Tehila Dahan, Kfir Y. Levy:
SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization. - Zaiquan Yang, Yuhao Liu, Jiaying Lin, Gerhard P. Hancke, Rynson W. H. Lau:
Boosting Weakly Supervised Referring Image Segmentation via Progressive Comprehension. - Leon Lang, Davis Foote, Stuart J. Russell, Anca D. Dragan, Erik Jenner, Scott Emmons:
When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback. - Avinash Kori, Francesco Locatello, Ainkaran Santhirasekaram, Francesca Toni, Ben Glocker, Fabio De Sousa Ribeiro:
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention. - Andrea Bertazzi, Dario Shariatian, Umut Simsekli, Eric Moulines, Alain Durmus:
Piecewise deterministic generative models. - David H. Brookes, Jakub Otwinowski, Sam Sinai:
Contrastive losses as generalized models of global epistasis. - Samyak Jain, Ekdeep Singh Lubana, Kemal Oksuz, Tom Joy, Philip Torr, Amartya Sanyal, Puneet K. Dokania:
What Makes and Breaks Safety Fine-tuning? A Mechanistic Study. - Jieyi Bi, Yining Ma, Jianan Zhou, Wen Song, Zhiguang Cao, Yaoxin Wu, Jie Zhang:
Learning to Handle Complex Constraints for Vehicle Routing Problems. - Gavia Gray, Aman Tiwari, Shane Bergsma, Joel Hestness:
Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in Transformers. - Rui Duan, Mingjian Guang, Junli Wang, Chungang Yan, Hongda Qi, Wenkang Su, Can Tian, Haoran Yang:
Unifying Homophily and Heterophily for Spectral Graph Neural Networks via Triple Filter Ensembles. - Yixiu Mao, Qi Wang, Chen Chen, Yun Qu, Xiangyang Ji:
Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression. - Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth:
Dynamic Conditional Optimal Transport through Simulation-Free Flows. - Alberto Alfarano, François Charton, Amaury Hayat:
Global Lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers. - Zhikang Chen, Min Zhang, Sen Cui, Haoxuan Li, Gang Niu, Mingming Gong, Changshui Zhang, Kun Zhang:
Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization. - Xiaowen Ma, Zhenliang Ni, Xinghao Chen:
SSA-Seg: Semantic and Spatial Adaptive Pixel-level Classifier for Semantic Segmentation. - Mohamad Hakam Shams Eddin, Jürgen Gall:
Identifying Spatio-Temporal Drivers of Extreme Events. - Yixing Lao, Tao Tang, Xiaoyang Wu, Peng Chen, Kaicheng Yu, Hengshuang Zhao:
LiT: Unifying LiDAR "Languages" with LiDAR Translator. - Franziska Eberle, Felix Hommelsheim, Alexander Lindermayr, Zhenwei Liu, Nicole Megow, Jens Schlöter:
Accelerating Matroid Optimization through Fast Imprecise Oracles. - Lynn Le, Paolo Papale, Katja Seeliger, Antonio Lozano, Thirza Dado, Feng Wang, Pieter R. Roelfsema, Marcel A. J. van Gerven, Yagmur Güçlütürk, Umut Güçlü:
MonkeySee: Space-time-resolved reconstructions of natural images from macaque multi-unit activity. - William Huang, Yifeng Jiang, Tom Van Wouwe, C. Karen Liu:
Constrained Diffusion with Trust Sampling. - Liu Ziyin, Mingze Wang, Hongchao Li, Lei Wu:
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent. - Milena Gazdieva, Arip Asadulaev, Evgeny Burnaev, Aleksandr Korotin:
Light Unbalanced Optimal Transport. - Chaokang Jiang, Dalong Du, Jiuming Liu, Siting Zhu, Zhenqiang Liu, Zhuang Ma, Zhujin Liang, Jie Zhou:
NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolation. - Ruihao Xia, Yu Liang, Peng-Tao Jiang, Hao Zhang, Bo Li, Yang Tang, Pan Zhou:
Unsupervised Modality Adaptation with Text-to-Image Diffusion Models for Semantic Segmentation. - Mitchell Keren Taraday, Almog David, Chaim Baskin:
Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks. - Leyan Deng, Chenwang Wu, Defu Lian, Enhong Chen:
Learning from Highly Sparse Spatio-temporal Data. - Qi Bi, Jingjun Yi, Hao Zheng, Haolan Zhan, Yawen Huang, Wei Ji, Yuexiang Li, Yefeng Zheng:
Learning Frequency-Adapted Vision Foundation Model for Domain Generalized Semantic Segmentation. - Xun Wu, Shaohan Huang, Wenhui Wang, Shuming Ma, Li Dong, Furu Wei:
Multi-Head Mixture-of-Experts. - Markus Hiller, Krista A. Ehinger, Tom Drummond:
Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers. - Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari:
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization. - Dan Qiao, Kaiqi Zhang, Esha Singh, Daniel Soudry, Yu-Xiang Wang:
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes. - Eoin Delaney, Zihao Fu, Sandra Wachter, Brent D. Mittelstadt, Chris Russell:
OxonFair: A Flexible Toolkit for Algorithmic Fairness. - Kasper Green Larsen, Omar Montasser, Nikita Zhivotovskiy:
Derandomizing Multi-Distribution Learning. - Ran Ben-Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher, Shay Vargaftik:
Optimal and Approximate Adaptive Stochastic Quantization. - Junhan Kim, Chungman Lee, Eulrang Cho, Kyungphil Park, Ho-Young Kim, Joonyoung Kim, Yongkweon Jeon:
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers. - Pengcheng Chen, Jin Ye, Guoan Wang, Yanjun Li, Zhongying Deng, Wei Li, Tianbin Li, Haodong Duan, Ziyan Huang, Yanzhou Su, Benyou Wang, Shaoting Zhang, Bin Fu, Jianfei Cai, Bohan Zhuang, Eric J. Seibel, Junjun He, Yu Qiao:
GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI. - Kefan Su, Yusen Huo, Zhilin Zhang, Shuai Dou, Chuan Yu, Jian Xu, Zongqing Lu, Bo Zheng:
AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games. - Jeremy McMahan:
Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time. - Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Andrew Ilyas, Marzyeh Ghassemi, Aleksander Madry:
Improving Subgroup Robustness via Data Selection. - Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang:
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting. - Claudia Shi, Nicolas Beltran-Velez, Achille Nazaret, Carolina Zheng, Adrià Garriga-Alonso, Andrew Jesson, Maggie Makar, David M. Blei:
Hypothesis Testing the Circuit Hypothesis in LLMs. - Katherine Tieu, Dongqi Fu, Yada Zhu, Hendrik F. Hamann, Jingrui He:
Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed. - Zhen-Yu Zhang, Zhiyu Xie, Huaxiu Yao, Masashi Sugiyama:
Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment. - Jinhong Lin, Cheng-En Wu, Yibing Wei, Pedro Morgado:
Accelerating Augmentation Invariance Pretraining. - Zhiqi Bu, Xinwei Zhang, Sheng Zha, Mingyi Hong, George Karypis:
Pre-training Differentially Private Models with Limited Public Data. - Heyang Zhao, Jiafan He, Quanquan Gu:
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation. - Garud Iyengar, Henry Lam, Tianyu Wang:
Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance? - Zelei Cheng, Xian Wu, Jiahao Yu, Shuo Han, Xin-Qiang Cai, Xinyu Xing:
Soft-Label Integration for Robust Toxicity Classification. - Yibo Wang, Sijia Chen, Wei Jiang, Wenhao Yang, Yuanyu Wan, Lijun Zhang:
Online Composite Optimization Between Stochastic and Adversarial Environments. - Chen Feng, Jay Zhuo, Parker Zhang, Ramchalam Kinattinkara Ramakrishnan, Zhaocong Yuan, Andrew Zou Li:
Stepping Forward on the Last Mile. - Zeyao Ma, Bohan Zhang, Jing Zhang, Jifan Yu, Xiaokang Zhang, Xiaohan Zhang, Sijia Luo, Xi Wang, Jie Tang:
SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation. - Kwangjun Ahn, Ashok Cutkosky:
Adam with model exponential moving average is effective for nonconvex optimization. - Alliot Nagle, Adway Girish, Marco Bondaschi, Michael Gastpar, Ashok Vardhan Makkuva, Hyeji Kim:
Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models. - Zhihao Li, Yufei Wang, Alex C. Kot, Bihan Wen:
From Chaos to Clarity: 3DGS in the Dark. - Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino:
RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks. - Liuyuan Jiang, Quan Xiao, Victor Tenorio, Fernando Real-Rojas, Antonio G. Marques, Tianyi Chen:
A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints. - Roland Stolz, Hanna Krasowski, Jakob Thumm, Michael Eichelbeck, Philipp Gassert, Matthias Althoff:
Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking. - Ke Wang, Junting Pan, Weikang Shi, Zimu Lu, Houxing Ren, Aojun Zhou, Mingjie Zhan, Hongsheng Li:
Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset. - Zigeng Chen, Xinyin Ma, Gongfan Fang, Zhenxiong Tan, Xinchao Wang:
AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising. - Jaihoon Kim, Juil Koo, Kyeongmin Yeo, Minhyuk Sung:
SyncTweedies: A General Generative Framework Based on Synchronized Diffusions. - Boshi Wang, Xiang Yue, Yu Su, Huan Sun:
Grokking of Implicit Reasoning in Transformers: A Mechanistic Journey to the Edge of Generalization. - Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, Tianle Li, Max Ku, Kai Wang, Alex Zhuang, Rongqi Fan, Xiang Yue, Wenhu Chen:
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark. - Xianghua Zeng, Hao Peng, Angsheng Li:
Effective Exploration Based on the Structural Information Principles. - Jialin Li, Marta Zagórowska, Giulia De Pasquale, Alisa Rupenyan, John Lygeros:
Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel. - Zicheng Sun, Yixuan Zhang, Zenan Ling, Xuhui Fan, Feng Zhou:
Nonstationary Sparse Spectral Permanental Process. - Avelina Asada Hadji-Kyriacou, Ognjen Arandjelovic:
Would I Lie To You? Inference Time Alignment of Language Models using Direct Preference Heads. - Chenyi Zi, Haihong Zhao, Xiangguo Sun, Yiqing Lin, Hong Cheng, Jia Li:
ProG: A Graph Prompt Learning Benchmark. - Vivek Sivaraman Narayanaswamy, Kowshik Thopalli, Rushil Anirudh, Yamen Mubarka, Wesam Sakla, Jayaraman J. Thiagarajan:
On the Use of Anchoring for Training Vision Models. - Chun-Mao Lai, Hsiang-Chun Wang, Ping-Chun Hsieh, Yu-Chiang Frank Wang, Min-Hung Chen, Shao-Hua Sun:
Diffusion-Reward Adversarial Imitation Learning. - Zirui Liu, Yan Zhuang, Qi Liu, Jiatong Li, Yuren Zhang, Zhenya Huang, Jinze Wu, Shijin Wang:
Computerized Adaptive Testing via Collaborative Ranking. - Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yian Ma, Tong Zhang:
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference. - Junlin He, Jinxiao Du, Wei Ma:
Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization. - Thibaut Germain, Samuel Gruffaz, Charles Truong, Alain Durmus, Laurent Oudre:
Shape analysis for time series. - Megha Srivastava, Simran Arora, Dan Boneh:
Optimistic Verifiable Training by Controlling Hardware Nondeterminism. - Mauricio Velasco, Kaiying O'Hare, Bernardo Rychtenberg, Soledad Villar:
Graph neural networks and non-commuting operators. - Shengyun Peng, Pin-Yu Chen, Matthew Hull, Duen Horng Chau:
Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models. - Qianqian Xie, Weiguang Han, Zhengyu Chen, Ruoyu Xiang, Xiao Zhang, Yueru He, Mengxi Xiao, Dong Li, Yongfu Dai, Duanyu Feng, Yijing Xu, Haoqiang Kang, Ziyan Kuang, Chenhan Yuan, Kailai Yang, Zheheng Luo, Tianlin Zhang, Zhiwei Liu, Guojun Xiong, Zhiyang Deng, Yuechen Jiang, Zhiyuan Yao, Haohang Li, Yangyang Yu, Gang Hu, Jiajia Huang, Xiao-Yang Liu, Alejandro Lopez-Lira, Benyou Wang, Yanzhao Lai, Hao Wang, Min Peng, Sophia Ananiadou, Jimin Huang:
FinBen: A Holistic Financial Benchmark for Large Language Models. - Zhihao Shu, Xiaowei Yu, Zihao Wu, Wenqi Jia, Yinchen Shi, Miao Yin, Tianming Liu, Dajiang Zhu, Wei Niu:
Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices. - Benjamin Cohen-Wang, Harshay Shah, Kristian Georgiev, Aleksander Madry:
ContextCite: Attributing Model Generation to Context. - Christina Bukas, Harshavardhan Subramanian, Fenja See, Carina Steinchen, Ivan Ezhov, Gowtham Boosarpu, Sara Asgharpour, Gerald Burgstaller, Mareike Lehmann, Florian Kofler, Marie Piraud:
MultiOrg: A Multi-rater Organoid-detection Dataset. - Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter, Volkan Cevher, John Lygeros:
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces. - Su Zheng, Zhengqi Gao, Fan-Keng Sun, Duane S. Boning, Bei Yu, Martin D. F. Wong:
Improving Neural ODE Training with Temporal Adaptive Batch Normalization. - Andrej Tschalzev, Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt:
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data. - Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang, Kyungho Kim, Jaemin Yoo, Kijung Shin:
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy. - Yubo Ma, Yuhang Zang, Liangyu Chen, Meiqi Chen, Yizhu Jiao, Xinze Li, Xinyuan Lu, Ziyu Liu, Yan Ma, Xiaoyi Dong, Pan Zhang, Liangming Pan, Yu-Gang Jiang, Jiaqi Wang, Yixin Cao, Aixin Sun:
MMLONGBENCH-DOC: Benchmarking Long-context Document Understanding with Visualizations. - Ilya A. Kuruzov, Gesualdo Scutari, Alexander V. Gasnikov:
Achieving Linear Convergence with Parameter-Free Algorithms in Decentralized Optimization. - Thomas E. Yerxa, Jenelle Feather, Eero P. Simoncelli, SueYeon Chung:
Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT. - Andrew Lowy, Daogao Liu, Hilal Asi:
Faster Algorithms for User-Level Private Stochastic Convex Optimization. - Yue Liu, Shihao Zhu, Tianyuan Yang, Jian Ma, Wenliang Zhong:
Identify Then Recommend: Towards Unsupervised Group Recommendation. - Wufei Ma, Guofeng Zhang, Qihao Liu, Guanning Zeng, Adam Kortylewski, Yaoyao Liu, Alan L. Yuille:
ImageNet3D: Towards General-Purpose Object-Level 3D Understanding. - Yoni Kasten, Wuyue Lu, Haggai Maron:
Fast Encoder-Based 3D from Casual Videos via Point Track Processing. - Wen-Hsuan Chu, Lei Ke, Katerina Fragkiadaki:
DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular Videos. - Riccardo Rende, Federica Gerace, Alessandro Laio, Sebastian Goldt:
A distributional simplicity bias in the learning dynamics of transformers. - Jincen Jiang, Qianyu Zhou, Yuhang Li, Xinkui Zhao, Meili Wang, Lizhuang Ma, Jian Chang, Jian Jun Zhang, Xuequan Lu:
PCoTTA: Continual Test-Time Adaptation for Multi-Task Point Cloud Understanding. - Artin Tajdini, Lalit Jain, Kevin G. Jamieson:
Nearly Minimax Optimal Submodular Maximization with Bandit Feedback. - Victor Boutin, Rishav Mukherji, Aditya Agrawal, Sabine Muzellec, Thomas Fel, Thomas Serre, Rufin VanRullen:
Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks. - Samuel Holt, Zhaozhi Qian, Tennison Liu, James Weatherall, Mihaela van der Schaar:
Data-Driven Discovery of Dynamical Systems in Pharmacology using Large Language Models. - Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen:
Improved Generation of Adversarial Examples Against Safety-aligned LLMs. - Yihua Zhang, Chongyu Fan, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Gaoyuan Zhang, Gaowen Liu, Ramana Kompella, Xiaoming Liu, Sijia Liu:
UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models. - Lu Yu, Haiyang Zhang, Changsheng Xu:
Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models. - Hejie Cui, Lingjun Mao, Xin Liang, Jieyu Zhang, Hui Ren, Quanzheng Li, Xiang Li, Carl Yang:
Biomedical Visual Instruction Tuning with Clinician Preference Alignment. - Linfeng Dong, Wei Wang, Yu Qiao, Xiao Sun:
LucidAction: A Hierarchical and Multi-model Dataset for Comprehensive Action Quality Assessment. - Zilong Huang, Qinghao Ye, Bingyi Kang, Jiashi Feng, Haoqi Fan:
Classification Done Right for Vision-Language Pre-Training. - Christopher Wang, Adam Uri Yaari, Aaditya Singh, Vighnesh Subramaniam, Dana Rosenfarb, Jan DeWitt, Pranav Misra, Joseph R. Madsen, Scellig S. Stone, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu:
Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli. - Jiangshan Wang, Yue Ma, Jiayi Guo, Yicheng Xiao, Gao Huang, Xiu Li:
COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing. - Dmitry Kovalev, Ekaterina Borodich, Alexander V. Gasnikov, Dmitrii Feoktistov:
Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks. - Jitesh Joshi, Sos S. Agaian, Youngjun Cho:
FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing. - Haoang Chi, He Li, Wenjing Yang, Feng Liu, Long Lan, Xiaoguang Ren, Tongliang Liu, Bo Han:
Unveiling Causal Reasoning in Large Language Models: Reality or Mirage? - Felix Dangel:
Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods. - Jintao Tong, Yixiong Zou, Yuhua Li, Ruixuan Li:
Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation. - Pascal Bergsträßer, Chris Köcher, Anthony Widjaja Lin, Georg Zetzsche:
The Power of Hard Attention Transformers on Data Sequences: A formal language theoretic perspective. - Xiao Zhang, William Gao, Seemandhar Jain, Michael Maire, David A. Forsyth, Anand Bhattad:
Latent Intrinsics Emerge from Training to Relight. - Chang Gao, Haiyun Jiang, Deng Cai, Shuming Shi, Wai Lam:
StrategyLLM: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving. - Daniela de Albuquerque, John M. Pearson:
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models. - Spencer Rooke, Zhaoze Wang, Ronald W. Di Tullio, Vijay Balasubramanian:
Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes. - Jovin Leong, Koa Di, Benjamin Cham, Shaun Heng:
SHDocs: A dataset, benchmark, and method to efficiently generate high-quality, real-world specular highlight data with near-perfect alignment. - Chuanyi Xue, Qihan Liu, Xiaoteng Ma, Xinyao Qin, Gui Ning, Yang Qi, Jinsheng Ren, Bin Liang, Jun Yang:
NeuralPlane: An Efficiently Parallelizable Platform for Fixed-wing Aircraft Control with Reinforcement Learning. - Xinchen Zhang, Ling Yang, Yaqi Cai, Zhaochen Yu, Kai-Ni Wang, Jiake Xie, Ye Tian, Minkai Xu, Yong Tang, Yujiu Yang, Bin Cui:
RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models. - Zhicheng Sun, Zhenhao Yang, Yang Jin, Haozhe Chi, Kun Xu, Liwei Chen, Hao Jiang, Yang Song, Kun Gai, Yadong Mu:
RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance. - Jay Bear, Adam Prügel-Bennett, Jonathon Hare:
Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints. - Jen-tse Huang, Man Ho Lam, Eric John Li, Shujie Ren, Wenxuan Wang, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu:
Apathetic or Empathetic? Evaluating LLMs' Emotional Alignments with Humans. - Matthew Ashman, Cristiana Diaconu, Adrian Weller, Wessel P. Bruinsma, Richard E. Turner:
Approximately Equivariant Neural Processes. - Mingjia Li, Shuo Liu, Hong Qian, Aimin Zhou:
A Simple yet Scalable Granger Causal Structural Learning Approach for Topological Event Sequences. - Sijin Chen, Xin Chen, Anqi Pang, Xianfang Zeng, Wei Cheng, Yijun Fu, Fukun Yin, Billzb Wang, Jingyi Yu, Gang Yu, Bin Fu, Tao Chen:
MeshXL: Neural Coordinate Field for Generative 3D Foundation Models. - Francesca Babiloni, Alexandros Lattas, Jiankang Deng, Stefanos Zafeiriou:
ID-to-3D: Expressive ID-guided 3D Heads via Score Distillation Sampling. - Youwei Lyu, Heng Guo, Kailong Zhang, Si Li, Boxin Shi:
SfPUEL: Shape from Polarization under Unknown Environment Light. - Qi Wang, Junming Yang, Yunbo Wang, Xin Jin, Wenjun Zeng, Xiaokang Yang:
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning. - Aymeric Capitaine, Etienne Boursier, Antoine Scheid, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Durmus:
Unravelling in Collaborative Learning. - Tri Nguyen, Shahana Ibrahim, Xiao Fu:
Noisy Label Learning with Instance-Dependent Outliers: Identifiability via Crowd Wisdom. - Cheng Luo, Jiawei Zhao, Zhuoming Chen, Beidi Chen, Animashree Anandkumar:
Mini-Sequence Transformers: Optimizing Intermediate Memory for Long Sequences Training. - Rui Peng, Wangze Xu, Luyang Tang, Levio Leo, Jianbo Jiao, Ronggang Wang:
Structure Consistent Gaussian Splatting with Matching Prior for Few-shot Novel View Synthesis. - Guanghao Zheng, Yuchen Liu, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong:
MC-DiT: Contextual Enhancement via Clean-to-Clean Reconstruction for Masked Diffusion Models. - André F. Cruz, Moritz Hardt, Celestine Mendler-Dünner:
Evaluating language models as risk scores. - Yazid Janati, Badr Moufad, Alain Durmus, Eric Moulines, Jimmy Olsson:
Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors. - Bowen Zhang, Yiji Cheng, Jiaolong Yang, Chunyu Wang, Feng Zhao, Yansong Tang, Dong Chen, Baining Guo:
GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling. - Fuli Qiao, Mehrdad Mahdavi:
Learn more, but bother less: parameter efficient continual learning. - Zhen Zhao, Jingqun Tang, Binghong Wu, Chunhui Lin, Shu Wei, Hao Liu, Xin Tan, Zhizhong Zhang, Can Huang, Yuan Xie:
Harmonizing Visual Text Comprehension and Generation. - Runze You, Shi Pu:
B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data. - Wenlin Chen, Hong Ge:
Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks. - Erdi Sayar, Giovanni Iacca, Ozgur S. Oguz, Alois Knoll:
Diffusion-based Curriculum Reinforcement Learning. - David Brandfonbrener, Hanlin Zhang, Andreas Kirsch, Jonathan Richard Schwarz, Sham M. Kakade:
CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training. - Yuankai Luo, Lei Shi, Xiao-Ming Wu:
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification. - Xuanchi Ren, Yifan Lu, Hanxue Liang, Jay Zhangjie Wu, Huan Ling, Mike Chen, Sanja Fidler, Francis Williams, Jiahui Huang:
SCube: Instant Large-Scale Scene Reconstruction using VoxSplats. - Simina Brânzei, MohammadTaghi Hajiaghayi, Reed Phillips, Suho Shin, Kun Wang:
Dueling over Dessert, Mastering the Art of Repeated Cake Cutting. - Qiyuan He, Jinghao Wang, Ziwei Liu, Angela Yao:
AID: Attention Interpolation of Text-to-Image Diffusion. - Liangxin Liu, Xuebo Liu, Derek F. Wong, Dongfang Li, Ziyi Wang, Baotian Hu, Min Zhang:
SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection. - Dora Zhao, Morgan Klaus Scheuerman, Pooja Chitre, Jerone Theodore Alexander Andrews, Georgia Panagiotidou, Shawn Walker, Kathleen H. Pine, Alice Xiang:
A Taxonomy of Challenges to Curating Fair Datasets. - Chengyu Fang, Chunming He, Fengyang Xiao, Yulun Zhang, Longxiang Tang, Yuelin Zhang, Kai Li, Xiu Li:
Real-world Image Dehazing with Coherence-based Pseudo Labeling and Cooperative Unfolding Network. - Ximing Li, Silong Liang, Changchun Li, Pengfei Wang, Fangming Gu:
Semi-supervised Multi-label Learning with Balanced Binary Angular Margin Loss. - Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu:
Statistical-Computational Trade-offs for Density Estimation. - Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
Benchmarking the Attribution Quality of Vision Models. - Renhong Huang, Jiarong Xu, Zhiming Yang, Xiang Si, Xin Jiang, Hanyang Yuan, Chunping Wang, Yang Yang:
Extracting Training Data from Molecular Pre-trained Models. - Marek Eliás, Haim Kaplan, Yishay Mansour, Shay Moran:
Learning-Augmented Algorithms with Explicit Predictors. - Zichao Li, Yanshuai Cao, Jackie CK Cheung:
Do LLMs Build World Representations? Probing Through the Lens of State Abstraction. - Mark Blacher, Christoph Staudt, Julien Klaus, Maurice Wenig, Niklas Merk, Alexander Breuer, Max Engel, Sören Laue, Joachim Giesen:
Einsum Benchmark: Enabling the Development of Next-Generation Tensor Execution Engines. - Timothy Nguyen:
Understanding Transformers via N-Gram Statistics. - Guobin Shen, Dongcheng Zhao, Xiang He, Linghao Feng, Yiting Dong, Jihang Wang, Qian Zhang, Yi Zeng:
Neuro-Vision to Language: Enhancing Brain Recording-based Visual Reconstruction and Language Interaction. - Federico Barbero, Andrea Banino, Steven Kapturowski, Dharshan Kumaran, João Guilherme Madeira Araújo, Oleksandr Vitvitskyi, Razvan Pascanu, Petar Velickovic:
Transformers need glasses! Information over-squashing in language tasks. - Christoph Jansen, Georg Schollmeyer, Julian Rodemann, Hannah Blocher, Thomas Augustin:
Statistical Multicriteria Benchmarking via the GSD-Front. - Jinjie Ni, Fuzhao Xue, Xiang Yue, Yuntian Deng, Mahir Shah, Kabir Jain, Graham Neubig, Yang You:
MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures. - Zhuoran Jin, Pengfei Cao, Chenhao Wang, Zhitao He, Hongbang Yuan, Jiachun Li, Yubo Chen, Kang Liu, Jun Zhao:
RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models. - James T. Wilson:
Stopping Bayesian Optimization with Probabilistic Regret Bounds. - Jiaheng Liu, Chenchen Zhang, Jinyang Guo, Yuanxing Zhang, Haoran Que, Ken Deng, Zhiqi Bai, Jie Liu, Ge Zhang, Jiakai Wang, Yanan Wu, Congnan Liu, Jiamang Wang, Lin Qu, Wenbo Su, Bo Zheng:
DDK: Distilling Domain Knowledge for Efficient Large Language Models. - Yuchen Fu, Zhiwei Jiang, Yuliang Liu, Cong Wang, Zexuan Deng, Zhaoling Chen, Qing Gu:
AP-Adapter: Improving Generalization of Automatic Prompts on Unseen Text-to-Image Diffusion Models. - Magauiya Zhussip, Iaroslav Koshelev, Stamatios Lefkimmiatis:
A Modular Conditional Diffusion Framework for Image Reconstruction. - Jing Wang, HaiYing Wang, Hao Zhang:
Scale-invariant Optimal Sampling for Rare-events Data and Sparse Models. - Yiwei Guo, Shaobin Zhuang, Kunchang Li, Yu Qiao, Yali Wang:
TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration. - Aviv Netanyahu, Yilun Du, Antonia Bronars, Jyothish Pari, Josh Tenenbaum, Tianmin Shu, Pulkit Agrawal:
Few-Shot Task Learning through Inverse Generative Modeling. - Yunnan Wang, Ziqiang Li, Wenyao Zhang, Zequn Zhang, Baao Xie, Xihui Liu, Wenjun Zeng, Xin Jin:
Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation. - Oliver Hamelijnck, Arno Solin, Theodoros Damoulas:
Physics-Informed Variational State-Space Gaussian Processes. - Alireza Abdollahpour, Mahed Abroshan, Seyed-Mohsen Moosavi-Dezfooli:
SuperDeepFool: a new fast and accurate minimal adversarial attack. - Youngsik Hwang, Dong-Young Lim:
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks. - Ayoub El Hanchi, Chris J. Maddison, Murat A. Erdogdu:
On the Efficiency of ERM in Feature Learning. - Zhibiao Wang, Xiao Wang, Haoyue Deng, Nian Liu, Shirui Pan, Chunming Hu:
Uncovering the Redundancy in Graph Self-supervised Learning Models. - Zhan Li, Yongtao Wu, Yihang Chen, Francesco Tonin, Elías Abad-Rocamora, Volkan Cevher:
Membership Inference Attacks against Large Vision-Language Models. - Deqing Fu, Tian-Qi Chen, Robin Jia, Vatsal Sharan:
Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression. - Weiquan Wang, Jun Xiao, Chunping Wang, Wei Liu, Zhao Wang, Long Chen:
$\text{Di}^2\text{Pose}$: Discrete Diffusion Model for Occluded 3D Human Pose Estimation. - Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller, Frank Hutter:
Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data. - Sukwon Yun, Inyoung Choi, Jie Peng, Yangfan Wu, Jingxuan Bao, Qiyiwen Zhang, Jiayi Xin, Qi Long, Tianlong Chen:
Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts. - Liyuan Mao, Haoran Xu, Xianyuan Zhan, Weinan Zhang, Amy Zhang:
Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning. - Andrew Jacobsen, Francesco Orabona:
An Equivalence Between Static and Dynamic Regret Minimization. - Ruoqi Zhang, Ziwei Luo, Jens Sjölund, Thomas B. Schön, Per Mattsson:
Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning. - Simone Rossetti, Fiora Pirri:
Hierarchy-Agnostic Unsupervised Segmentation: Parsing Semantic Image Structure. - Takashi Furuya, Michael Puthawala, Matti Lassas, Maarten V. de Hoop:
Can neural operators always be continuously discretized? - Hassan Ashtiani, Mahbod Majid, Shyam Narayanan:
Sample-Efficient Private Learning of Mixtures of Gaussians. - Jingnan Zheng, Han Wang, An Zhang, Tai D. Nguyen, Jun Sun, Tat-Seng Chua:
ALI-Agent: Assessing LLMs' Alignment with Human Values via Agent-based Evaluation. - Zhan Yu, Qiuhao Chen, Yuling Jiao, Yinan Li, Xiliang Lu, Xin Wang, Jerry Zhijian Yang:
Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits. - Chaochao Chen, Jiaming Zhang, Yizhao Zhang, Li Zhang, Lingjuan Lyu, Yuyuan Li, Biao Gong, Chenggang Yan:
CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence. - Kiyohiro Nakayama, Mikaela Angelina Uy, Yang You, Ke Li, Leonidas J. Guibas:
ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Field. - Shitong Shao, Zikai Zhou, Huanran Chen, Zhiqiang Shen:
Elucidating the Design Space of Dataset Condensation. - Zhihai Wang, Jie Wang, Qingyue Yang, Yinqi Bai, Xing Li, Lei Chen, Jianye Hao, Mingxuan Yuan, Bin Li, Yongdong Zhang, Feng Wu:
Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework. - Wenjie Mei, Dongzhe Zheng, Shihua Li:
ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence. - Ye Fang, Zeyi Sun, Tong Wu, Jiaqi Wang, Ziwei Liu, Gordon Wetzstein, Dahua Lin:
Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materials. - Chenjie Cao, Chaohui Yu, Fan Wang, Xiangyang Xue, Yanwei Fu:
MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing. - Lemei Zhang, Peng Liu, Marcus Tiedemann Oekland Henriksboe, Even W. Lauvrak, Jon Atle Gulla, Heri Ramampiaro:
PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models. - Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan, Darshan Thaker, Aditya Chattopadhyay, Chris Callison-Burch, René Vidal:
PaCE: Parsimonious Concept Engineering for Large Language Models. - Yexiao He, Ziyao Wang, Zheyu Shen, Guoheng Sun, Yucong Dai, Yongkai Wu, Hongyi Wang, Ang Li:
SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning. - Xianlong Wang, Minghui Li, Wei Liu, Hangtao Zhang, Shengshan Hu, Yechao Zhang, Ziqi Zhou, Hai Jin:
Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need. - Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng:
How to Solve Contextual Goal-Oriented Problems with Offline Datasets? - Youyuan Long, Tolga Ok, Pedro Zattoni Scroccaro, Peyman Mohajerin Esfahani:
Scalable Kernel Inverse Optimization. - Silpa Vadakkeeveetil Sreelatha, Adarsh Kappiyath, Abhra Chaudhuri, Anjan Dutta:
DeNetDM: Debiasing by Network Depth Modulation. - Shayan Kiyani, George J. Pappas, Hamed Hassani:
Length Optimization in Conformal Prediction. - Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee:
Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity. - Yuxuan Xue, Xianghui Xie, Riccardo Marin, Gerard Pons-Moll:
Human-3Diffusion: Realistic Avatar Creation via Explicit 3D Consistent Diffusion Models. - Chengshuai Shi, Kun Yang, Zihan Chen, Jundong Li, Jing Yang, Cong Shen:
Efficient Prompt Optimization Through the Lens of Best Arm Identification. - Peng Zhou, Rongwen Li, Liang Du:
Fair Kernel K-Means: from Single Kernel to Multiple Kernel. - Jiangming Shi, Xiangbo Yin, Yachao Zhang, Zhizhong Zhang, Yuan Xie, Yanyun Qu:
Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification. - Xiaowen Jiang, Anton Rodomanov, Sebastian U. Stich:
Stabilized Proximal-Point Methods for Federated Optimization. - Haolin Wang, Xuefeng Liu, Jianwei Niu, Wenkai Guo, Shaojie Tang:
Why Go Full? Elevating Federated Learning Through Partial Network Updates. - Yixin Ren, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou:
Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing. - Shengjie Niu, Lifan Lin, Jian Huang, Chao Wang:
OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning. - Frédéric Berdoz, Roger Wattenhofer:
Can an AI Agent Safely Run a Government? Existence of Probably Approximately Aligned Policies. - Linhan Wang, Kai Cheng, Shuo Lei, Shengkun Wang, Wei Yin, Chenyang Lei, Xiaoxiao Long, Chang-Tien Lu:
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos. - Hugo Chateau-Laurent, Frédéric Alexandre:
Relating Hopfield Networks to Episodic Control. - Yuli Wang, Peng jian, Yuwei Dai, Craig K. Jones, Haris I. Sair, Jinglai Shen, Nicolas Loizou, Jing Wu, Wen-Chi Hsu, Maliha Imami, Zhicheng Jiao, Paul Zhang, Harrison X. Bai:
Enhancing vision-language models for medical imaging: bridging the 3D gap with innovative slice selection. - Aahlad Manas Puli, Nhi Nguyen, Rajesh Ranganath:
Explanations that reveal all through the definition of encoding. - Chiu Wai Yan, Shi Quan Foo, Van-Hoang Trinh, Dit-Yan Yeung, Ka-Hing Wong, Wai-Kin Wong:
Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting. - Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang:
Robust Mixture Learning when Outliers Overwhelm Small Groups. - Jie Wang, Tingfa Xu, Lihe Ding, Jianan Li:
Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions. - Julian Dörfler, Benito van der Zander, Markus Bläser, Maciej Liskiewicz:
On the Complexity of Identification in Linear Structural Causal Models. - Arko Banerjee, Kia Rahmani, Joydeep Biswas, Isil Dillig:
Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning. - Max Ruiz Luyten, Mihaela van der Schaar:
A theoretical design of concept sets: improving the predictability of concept bottleneck models. - Yuxin Wang, Duanyu Feng, Yongfu Dai, Zhengyu Chen, Jimin Huang, Sophia Ananiadou, Qianqian Xie, Hao Wang:
HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection. - Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Pashmina Cameron, Martin Jaggi, Dan Alistarh, Torsten Hoefler, James Hensman:
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs. - Francisco Acosta, Fatih Dinc, William Redman, Manu S. Madhav, David A. Klindt, Nina Miolane:
Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems. - Enoch H. Kang, P. R. Kumar:
Is O(log N) practical? Near-Equivalence Between Delay Robustness and Bounded Regret in Bandits and RL. - Leying Zhang, Yao Qian, Long Zhou, Shujie Liu, Dongmei Wang, Xiaofei Wang, Midia Yousefi, Yanmin Qian, Jinyu Li, Lei He, Sheng Zhao, Michael Zeng:
CoVoMix: Advancing Zero-Shot Speech Generation for Human-like Multi-talker Conversations. - Adam Stooke, Rohit Prabhavalkar, Khe Chai Sim, Pedro Moreno Mengibar:
Aligner-Encoders: Self-Attention Transformers Can Be Self-Transducers. - Xu Yang, Yingzhe Peng, Haoxuan Ma, Shuo Xu, Chi Zhang, Yucheng Han, Hanwang Zhang:
Lever LM: Configuring In-Context Sequence to Lever Large Vision Language Models. - Junchao Wu, Runzhe Zhan, Derek F. Wong, Shu Yang, Xinyi Yang, Yulin Yuan, Lidia S. Chao:
DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarios. - Mingyang Liu, Xinyang Chen, Yang Shu, Xiucheng Li, Weili Guan, Liqiang Nie:
Boosting Transferability and Discriminability for Time Series Domain Adaptation. - Manling Li, Shiyu Zhao, Qineng Wang, Kangrui Wang, Yu Zhou, Sanjana Srivastava, Cem Gokmen, Tony Lee, Li Erran Li, Ruohan Zhang, Weiyu Liu, Percy Liang, Li Fei-Fei, Jiayuan Mao, Jiajun Wu:
Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making. - Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon:
Resolving Discrepancies in Compute-Optimal Scaling of Language Models. - Udaya Ghai, Karan Singh:
Sample-Efficient Agnostic Boosting. - Xiaoxuan Lei, Takuya Ito, Pouya Bashivan:
Geometry of naturalistic object representations in recurrent neural network models of working memory. - Avisek Naug, Antonio Guillen, Ricardo Luna Gutierrez, Vineet Gundecha, Cullen E. Bash, Sahand Ghorbanpour, Sajad Mousavi, Ashwin Ramesh Babu, Dejan Markovikj, Lekhapriya Dheeraj Kashyap, Desik Rengarajan, Soumyendu Sarkar:
SustainDC: Benchmarking for Sustainable Data Center Control. - Yura Malitsky, Konstantin Mishchenko:
Adaptive Proximal Gradient Method for Convex Optimization. - Cristóbal Eyzaguirre, Eric Tang, Shyamal Buch, Adrien Gaidon, Jiajun Wu, Juan Carlos Niebles:
Streaming Detection of Queried Event Start. - Shuo Liu, Kaining Ying, Hao Zhang, Yue Yang, Yuqi Lin, Tianle Zhang, Chuanhao Li, Yu Qiao, Ping Luo, Wenqi Shao, Kaipeng Zhang:
ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Ablation Capability for Large Vision-Language Models. - Yuchen Zhuang, Haotian Sun, Yue Yu, Rushi Qiang, Qifan Wang, Chao Zhang, Bo Dai:
HYDRA: Model Factorization Framework for Black-Box LLM Personalization. - Youssef Allouah, Abdellah El Mrini, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot:
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients. - Yuming Zhang, Jun-Wei Hsieh, Xin Li, Ming-Ching Chang, Chun-Chieh Lee, Kuo-Chin Fan:
MOTE-NAS: Multi-Objective Training-based Estimate for Efficient Neural Architecture Search. - Bora Yongacoglu, Gürdal Arslan, Lacra Pavel, Serdar Yüksel:
Paths to Equilibrium in Games. - Sangwon Jang, Jaehyeong Jo, Kimin Lee, Sung Ju Hwang:
Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models. - Wenkai Yang, Xiaohan Bi, Yankai Lin, Sishuo Chen, Jie Zhou, Xu Sun:
Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents. - Ali TehraniJamsaz, Arijit Bhattacharjee, Le Chen, Nesreen K. Ahmed, Amir Yazdanbakhsh, Ali Jannesari:
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming. - Alvaro H. C. Correia, Fabio Valerio Massoli, Christos Louizos, Arash Behboodi:
An Information Theoretic Perspective on Conformal Prediction. - Rajesh Jayaram, Laxman Dhulipala, Majid Hadian, Jason Lee, Vahab Mirrokni:
MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encoding. - Hongyang Li, Hao Zhang, Shilong Liu, Zhaoyang Zeng, Feng Li, Bohan Li, Tianhe Ren, Lei Zhang:
TAPTRv2: Attention-based Position Update Improves Tracking Any Point. - Lubo Wang, Di Lin, Kairui Yang, Ruonan Liu, Qing Guo, Wuyuan Xie, Miaohui Wang, Lingyu Liang, Yi Wang, Ping Li:
Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion. - Giannis Daras, Weili Nie, Karsten Kreis, Alex Dimakis, Morteza Mardani, Nikola B. Kovachki, Arash Vahdat:
Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models. - Ye Mao, Junpeng Jing, Krystian Mikolajczyk:
OpenDlign: Open-World Point Cloud Understanding with Depth-Aligned Images. - Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron:
A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening. - Yao Wu, Mingwei Xing, Yachao Zhang, Xiaotong Luo, Yuan Xie, Yanyun Qu:
UniDSeg: Unified Cross-Domain 3D Semantic Segmentation via Visual Foundation Models Prior. - Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar:
From Causal to Concept-Based Representation Learning. - Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland:
Foundations of Multivariate Distributional Reinforcement Learning. - Xiulong Liu, Kun Su, Eli Shlizerman:
Tell What You Hear From What You See - Video to Audio Generation Through Text. - Hongchao Zhang, Zhizhen Qin, Sicun Gao, Andrew Clark:
SEEV: Synthesis with Efficient Exact Verification for ReLU Neural Barrier Functions. - Rachel S. Y. Teo, Tan Nguyen:
Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis. - Haiyang Zheng, Nan Pu, Wenjing Li, Nicu Sebe, Zhun Zhong:
Prototypical Hash Encoding for On-the-Fly Fine-Grained Category Discovery. - Zuobai Zhang, Pascal Notin, Yining Huang, Aurélie C. Lozano, Vijil Chenthamarakshan, Debora S. Marks, Payel Das, Jian Tang:
Multi-Scale Representation Learning for Protein Fitness Prediction. - Ke Sun, Shen Chen, Taiping Yao, Hong Liu, Xiaoshuai Sun, Shouhong Ding, Rongrong Ji:
DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion. - Honglin Li, Yunlong Zhang, Pingyi Chen, Zhongyi Shui, Chenglu Zhu, Lin Yang:
Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis. - Dror Moran, Yuval Margalit, Guy Trostianetsky, Fadi Khatib, Meirav Galun, Ronen Basri:
Consensus Learning with Deep Sets for Essential Matrix Estimation. - Paul Krzakala, Junjie Yang, Rémi Flamary, Florence d'Alché-Buc, Charlotte Laclau, Matthieu Labeau:
Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss. - Fangqiang Ding, Xiangyu Wen, Yunzhou Zhu, Yiming Li, Chris Xiaoxuan Lu:
RadarOcc: Robust 3D Occupancy Prediction with 4D Imaging Radar. - Pengxiang Li, Zhi Gao, Bofei Zhang, Tao Yuan, Yuwei Wu, Mehrtash Harandi, Yunde Jia, Song-Chun Zhu, Qing Li:
FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models. - Yizhak Ben-Shabat, Chamin Hewa Koneputugodage, Sameera Ramasinghe, Stephen Gould:
Neural Experts: Mixture of Experts for Implicit Neural Representations. - Taira Tsuchiya, Shinji Ito:
Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets. - Saba Ahmadi, Kunhe Yang, Hanrui Zhang:
Strategic Littlestone Dimension: Improved Bounds on Online Strategic Classification. - Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang:
Transfer Q-star : Principled Decoding for LLM Alignment. - Tianxin Huang, Zhenyu Zhang, Ying Tai, Gim Hee Lee:
Learning to Decouple the Lights for 3D Face Texture Modeling. - Ruijie Zhu, Yanzhe Liang, Hanzhi Chang, Jiacheng Deng, Jiahao Lu, Wenfei Yang, Tianzhu Zhang, Yongdong Zhang:
MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting. - Jiachen Lian, Xuanru Zhou, Zoe Ezzes, Jet Vonk, Brittany Morin, David Baquirin, Zachary Miller, Maria Luisa Gorno-Tempini, Gopala Anumanchipalli:
SSDM: Scalable Speech Dysfluency Modeling. - Wenyuan Zhang, Yu-Shen Liu, Zhizhong Han:
Neural Signed Distance Function Inference through Splatting 3D Gaussians Pulled on Zero-Level Set. - Imanol Miranda, Ander Salaberria, Eneko Agirre, Gorka Azkune:
BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval. - Zecheng Hao, Xinyu Shi, Yujia Liu, Zhaofei Yu, Tiejun Huang:
LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model. - Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi (Richard) Zhang, Rajesh Ranganath, Kyunghyun Cho:
Preference Learning Algorithms Do Not Learn Preference Rankings. - Haizhong Zheng, Xiaoyan Bai, Xueshen Liu, Zhuoqing Morley Mao, Beidi Chen, Fan Lai, Atul Prakash:
Learn To be Efficient: Build Structured Sparsity in Large Language Models. - Chaoya Jiang, Hongrui Jia, Haiyang Xu, Wei Ye, Mengfan Dong, Ming Yan, Ji Zhang, Fei Huang, Shikun Zhang:
MaVEn: An Effective Multi-granularity Hybrid Visual Encoding Framework for Multimodal Large Language Model. - Qihang Fang, Chengcheng Tang, Bugra Tekin, Yanchao Yang:
CigTime: Corrective Instruction Generation Through Inverse Motion Editing. - Shengxiang Hu, Huaijiang Sun, Dong Wei, Xiaoning Sun, Jin Wang:
Continuous Heatmap Regression for Pose Estimation via Implicit Neural Representation. - Wei Dong, Yuan Sun, Yiting Yang, Xing Zhang, Zhijun Lin, Qingsen Yan, Haokui Zhang, Peng Wang, Yang Yang, Hengtao Shen:
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation. - Adrian Remonda, Nicklas Hansen, Ayoub Raji, Nicola Musiu, Marko Bertogna, Eduardo E. Veas, Xiaolong Wang:
A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data. - Chih-Hsuan Yang, Benjamin Feuer, Talukder Zaki Jubery, Zi K. Deng, Andre Nakkab, Md. Zahid Hasan, Shivani Chiranjeevi, Kelly O. Marshall, Nirmal Baishnab, Asheesh Kumar Singh, Arti Singh, Soumik Sarkar, Nirav C. Merchant, Chinmay Hegde, Baskar Ganapathysubramanian:
BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity. - Elias Jääsaari, Ville Hyvönen, Teemu Roos:
LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. - Daniel Severo, Ashish Khisti, Alireza Makhzani:
Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding. - Hanzhang Zhou, Zijian Feng, Zixiao Zhu, Junlang Qian, Kezhi Mao:
UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation. - Jingwei Zhao, Gus Xia, Ziyu Wang, Ye Wang:
Structured Multi-Track Accompaniment Arrangement via Style Prior Modelling. - Hui Chen, Yanbin Liu, Yongqiang Ma, Nanning Zheng, Xin Yu:
TPR: Topology-Preserving Reservoirs for Generalized Zero-Shot Learning. - Thomas Altstidl, David Dobre, Arthur Kosmala, Bjoern M. Eskofier, Gauthier Gidel, Leo Schwinn:
On the Scalability of Certified Adversarial Robustness with Generated Data. - Maximilian Nickel:
No Free Delivery Service: Epistemic limits of passive data collection in complex social systems. - Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang:
Discovery of the Hidden World with Large Language Models. - Zhi Cheng, Zhanhao Hu, Yuqiu Liu, Jianmin Li, Hang Su, Xiaolin Hu:
Full-Distance Evasion of Pedestrian Detectors in the Physical World. - Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora:
Can Models Learn Skill Composition from Examples? - Disha Makhija, Joydeep Ghosh, Nhat Ho:
A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings. - Lennert De Smet, Pedro Zuidberg Dos Martires:
A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetics. - Marian Longa, João F. Henriques:
Unsupervised Object Detection with Theoretical Guarantees. - Yunuo Chen, Tianyi Xie, Zeshun Zong, Xuan Li, Feng Gao, Yin Yang, Ying Nian Wu, Chenfanfu Jiang:
Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication. - Damien Ferbach, Quentin Bertrand, Avishek Joey Bose, Gauthier Gidel:
Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences. - Xi Yang, Xu Gu, Xingyilang Yin, Xinbo Gao:
SA3DIP: Segment Any 3D Instance with Potential 3D Priors. - Ziquan Ou, Zijun Zhang:
CODA: A Correlation-Oriented Disentanglement and Augmentation Modeling Scheme for Better Resisting Subpopulation Shifts. - Junyuan Zhang, Songhua Liu, Xinchao Wang:
One-shot Federated Learning via Synthetic Distiller-Distillate Communication. - Josh Givens, Henry W. J. Reeve, Song Liu, Katarzyna Reluga:
Conditional Outcome Equivalence: A Quantile Alternative to CATE. - Yiman Hu, Yixiong Zou, Ruixuan Li, Yuhua Li:
Generate Universal Adversarial Perturbations for Few-Shot Learning. - Lorenzo Noci, Alexandru Meterez, Thomas Hofmann, Antonio Orvieto:
Super Consistency of Neural Network Landscapes and Learning Rate Transfer. - Dingbang Liu, Shohei Kato, Wen Gu, Fenghui Ren, Jun Yan, Guoxin Su:
Integrating Suboptimal Human Knowledge with Hierarchical Reinforcement Learning for Large-Scale Multiagent Systems. - Haowei Zhu, Ling Yang, Jun-Hai Yong, Hongzhi Yin, Jiawei Jiang, Meng Xiao, Wentao Zhang, Bin Wang:
Distribution-Aware Data Expansion with Diffusion Models. - Ryan Welch, Jiaqi Zhang, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data. - Dongyang Li, Chen Wei, Shiying Li, Jiachen Zou, Quanying Liu:
Visual Decoding and Reconstruction via EEG Embeddings with Guided Diffusion. - Yashas Malur Saidutta, Rakshith Sharma Srinivasa, Jaejin Cho, Ching Hua Lee, Chouchang Yang, Yilin Shen, Hongxia Jin:
CIFD: Controlled Information Flow to Enhance Knowledge Distillation. - Bavesh Balaji, Jerrin Bright, Yuhao Chen, Sirisha Rambhatla, John S. Zelek, David A. Clausi:
Seeing Beyond the Crop: Using Language Priors for Out-of-Bounding Box Keypoint Prediction. - Liang Chen, Yong Zhang, Yibing Song, Zhiqiang Shen, Lingqiao Liu:
LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization. - Xuefeng Du, Chaowei Xiao, Sharon Li:
HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection. - Miria Feng, Zachary Frangella, Mert Pilanci:
CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks. - Enrique B. Nueve, Dhamma Kimpara, Bo Waggoner, Jessica Finocchiaro:
Trading off Consistency and Dimensionality of Convex Surrogates for Multiclass Classification. - Yue Liu, Yunjie Tian, Yuzhong Zhao, Hongtian Yu, Lingxi Xie, Yaowei Wang, Qixiang Ye, Jianbin Jiao, Yunfan Liu:
VMamba: Visual State Space Model. - Xin Jin, Qianqian Qiao, Yi Lu, Huaye Wang, Heng Huang, Shan Gao, Jianfei Liu, Rui Li:
APDDv2: Aesthetics of Paintings and Drawings Dataset with Artist Labeled Scores and Comments. - Ming Yang, Yuzheng Cai, Weiguo Zheng:
CSPG: Crossing Sparse Proximity Graphs for Approximate Nearest Neighbor Search. - Baao Xie, Qiuyu Chen, Yunnan Wang, Zequn Zhang, Xin Jin, Wenjun Zeng:
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models. - Jiaxin Shi, Kehang Han, Zhe Wang, Arnaud Doucet, Michalis K. Titsias:
Simplified and Generalized Masked Diffusion for Discrete Data. - Yifan Wang, Di Huang, Weicai Ye, Guofeng Zhang, Wanli Ouyang, Tong He:
NeuRodin: A Two-stage Framework for High-Fidelity Neural Surface Reconstruction. - Nirmit Joshi, Theodor Misiakiewicz, Nati Srebro:
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries. - Zhaochen Su, Jun Zhang, Xiaoye Qu, Tong Zhu, Yanshu Li, Jiashuo Sun, Juntao Li, Min Zhang, Yu Cheng:
ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLMs. - Kyungmin Lee, Sangkyung Kwak, Kihyuk Sohn, Jinwoo Shin:
Direct Consistency Optimization for Robust Customization of Text-to-Image Diffusion models. - Zhuofan Zong, Bingqi Ma, Dazhong Shen, Guanglu Song, Hao Shao, Dongzhi Jiang, Hongsheng Li, Yu Liu:
MoVA: Adapting Mixture of Vision Experts to Multimodal Context. - Jiacong Xu, Yiqun Mei, Vishal M. Patel:
Wild-GS: Real-Time Novel View Synthesis from Unconstrained Photo Collections. - Giovanni Bellitto, Federica Proietto Salanitri, Matteo Pennisi, Matteo Boschini, Lorenzo Bonicelli, Angelo Porrello, Simone Calderara, Simone Palazzo, Concetto Spampinato:
Saliency-driven Experience Replay for Continual Learning. - Valentin De Bortoli, Iryna Korshunova, Andriy Mnih, Arnaud Doucet:
Schrodinger Bridge Flow for Unpaired Data Translation. - Kai Zhao, Xuhao Li, Qiyu Kang, Feng Ji, Qinxu Ding, Yanan Zhao, Wenfei Liang, Wee Peng Tay:
Distributed-Order Fractional Graph Operating Network. - Pengchao Han, Chao Huang, Geng Tian, Ming Tang, Xin Liu:
Convergence Analysis of Split Federated Learning on Heterogeneous Data. - Zhibin Gu, Songhe Feng:
From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement. - Haochen Li, Rui Zhang, Hantao Yao, Xin Zhang, Yifan Hao, Xinkai Song, Xiaqing Li, Yongwei Zhao, Yunji Chen, Ling Li:
DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection. - Zhixing Zhang, Yanyu Li, Yushu Wu, Yanwu Xu, Anil Kag, Ivan Skorokhodov, Willi Menapace, Aliaksandr Siarohin, Junli Cao, Dimitris N. Metaxas, Sergey Tulyakov, Jian Ren:
SF-V: Single Forward Video Generation Model. - Batuhan Tömekçe, Mark Vero, Robin Staab, Martin T. Vechev:
Private Attribute Inference from Images with Vision-Language Models. - Allen Nie, Yash Chandak, Christina J. Yuan, Anirudhan Badrinath, Yannis Flet-Berliac, Emma Brunskill:
OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators. - Xiangyu Chen, Zhenzhen Liu, Katie Luo, Siddhartha Datta, Adhitya Polavaram, Yan Wang, Yurong You, Boyi Li, Marco Pavone, Wei-Lun Chao, Mark E. Campbell, Bharath Hariharan, Kilian Q. Weinberger:
DiffuBox: Refining 3D Object Detection with Point Diffusion. - Jan van Delden, Julius Schultz, Christopher Blech, Sabine C. Langer, Timo Lüddecke:
Learning to Predict Structural Vibrations. - Qi Jia, Baoyu Fan, Cong Xu, Lu Liu, Liang Jin, Guoguang Du, Zhenhua Guo, Yaqian Zhao, Xuanjing Huang, Rengang Li:
Infer Induced Sentiment of Comment Response to Video: A New Task, Dataset and Baseline. - Dongwon Kim, Seoyeon Kim, Suha Kwak:
Bootstrapping Top-down Information for Self-modulating Slot Attention. - Muning Wen, Ziyu Wan, Jun Wang, Weinan Zhang, Ying Wen:
Reinforcing LLM Agents via Policy Optimization with Action Decomposition. - Jiamian Wang, Zongliang Wu, Yulun Zhang, Xin Yuan, Tao Lin, Zhiqiang Tao:
Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging. - Andi Han, Bamdev Mishra, Pratik Kumar Jawanpuria, Akiko Takeda:
A Framework for Bilevel Optimization on Riemannian Manifolds. - Szymon Antoniak, Michal Krutul, Maciej Pióro, Jakub Krajewski, Jan Ludziejewski, Kamil Ciebiera, Krystian Król, Tomasz Odrzygózdz, Marek Cygan, Sebastian Jaszczur:
Mixture of Tokens: Continuous MoE through Cross-Example Aggregation. - Dominik Klein, Théo Uscidda, Fabian J. Theis, Marco Cuturi:
GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics. - Shubham Kumar Bharti, Stephen Wright, Adish Singla, Xiaojin (Jerry) Zhu:
On the Complexity of Teaching a Family of Linear Behavior Cloning Learners. - Felix Petersen, Christian Borgelt, Stefano Ermon:
TrAct: Making First-layer Pre-Activations Trainable. - Mengke Li, Ye Liu, Yang Lu, Yiqun Zhang, Yiu-Ming Cheung, Hui Huang:
Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition. - Mingming Ha, Taoxuewen, Wenfang Lin, Qiongxu Ma, Wujiang Xu, Linxun Chen:
Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random. - Md. Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel V. Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Animashree Anandkumar:
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. - Hanxi Guo, Siyuan Cheng, Xiaolong Jin, Zhuo Zhang, Kaiyuan Zhang, Guanhong Tao, Guangyu Shen, Xiangyu Zhang:
BiScope: AI-generated Text Detection by Checking Memorization of Preceding Tokens. - Wenjie Xu, Masaki Adachi, Colin N. Jones, Michael A. Osborne:
Principled Bayesian Optimization in Collaboration with Human Experts. - Dengwei Zhao, Shikui Tu, Lei Xu:
SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling. - Nikita Kornilov, Petr Mokrov, Alexander V. Gasnikov, Alexander Korotin:
Optimal Flow Matching: Learning Straight Trajectories in Just One Step. - Veeti Ahvonen, Damian Heiman, Antti Kuusisto, Carsten Lutz:
Logical characterizations of recurrent graph neural networks with reals and floats. - Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi S. Jaakkola, Stefanie Jegelka:
In-Context Symmetries: Self-Supervised Learning through Contextual World Models. - Ming Xiang, Stratis Ioannidis, Edmund Yeh, Carlee Joe-Wong, Lili Su:
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability. - Peihua Mai, Ran Yan, Yan Pang:
RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation. - Ziqian Zhong, Jacob Andreas:
Algorithmic Capabilities of Random Transformers. - Alberto Cabezas, Louis Sharrock, Christopher Nemeth:
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows. - Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jarret Ross:
Distributional Preference Alignment of LLMs via Optimal Transport. - Yenho Chen, Noga Mudrik, Kyle A. Johnsen, Sankaraleengam Alagapan, Adam S. Charles, Christopher Rozell:
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics. - Akifumi Wachi, Thien Q. Tran, Rei Sato, Takumi Tanabe, Youhei Akimoto:
Stepwise Alignment for Constrained Language Model Policy Optimization. - Tiansheng Huang, Sihao Hu, Fatih Ilhan, Selim F. Tekin, Ling Liu:
Lisa: Lazy Safety Alignment for Large Language Models against Harmful Fine-tuning Attack. - Alexis Bellot, Silvia Chiappa:
Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding. - Yiling Chen, Shi Feng, Fang-Yi Yu:
Carrot and Stick: Eliciting Comparison Data and Beyond. - Leonardo Defilippis, Bruno Loureiro, Theodor Misiakiewicz:
Dimension-free deterministic equivalents and scaling laws for random feature regression. - Matthew J. Allen, Francisco Dorr, Joseph Alejandro Gallego Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán:
M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data. - Yizhou Zhao, Hengwei Bian, Kaihua Chen, Pengliang Ji, Liao Qu, Shao-yu Lin, Weichen Yu, Haoran Li, Hao Chen, Jun Shen, Bhiksha Raj, Min Xu:
Metric from Human: Zero-shot Monocular Metric Depth Estimation via Test-time Adaptation. - Allan Zhou, Chelsea Finn, James Harrison:
Universal Neural Functionals. - Jingbo Zhou, Shaorong Chen, Jun Xia, Sizhe Liu, Tianze Ling, Wenjie Du, Yue Liu, Jianwei Yin, Stan Z. Li:
NovoBench: Benchmarking Deep Learning-based \emph{De Novo} Sequencing Methods in Proteomics. - Gaochao Song, Chong Cheng, Hao Wang:
GVKF: Gaussian Voxel Kernel Functions for Highly Efficient Surface Reconstruction in Open Scenes. - Yaohua Zha, Naiqi Li, Yanzi Wang, Tao Dai, Hang Guo, Bin Chen, Zhi Wang, Zhihao Ouyang, Shu-Tao Xia:
LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling. - Adam Li, Yushu Pan, Elias Bareinboim:
Disentangled Representation Learning in Non-Markovian Causal Systems. - Yi-Fan Zhang, Min-Ling Zhang:
Generalization Analysis for Label-Specific Representation Learning. - Anindya Sarkar, Srikumar Sastry, Aleksis Pirinen, Chongjie Zhang, Nathan Jacobs, Yevgeniy Vorobeychik:
GOMAA-Geo: GOal Modality Agnostic Active Geo-localization. - Hao Wu, Changhu Wang, Fan Xu, Jinbao Xue, Chong Chen, Xian-Sheng Hua, Xiao Luo:
PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling. - Martín Bertran, Shuai Tang, Michael Kearns, Jamie H. Morgenstern, Aaron Roth, Steven Z. Wu:
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable. - Yiquan Li, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Jiachen Lei, Bo Li, Chaowei Xiao:
Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness. - Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar:
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner. - Kexue Fu, Xiaoyuan Luo, Linhao Qu, Shuo Wang, Ying Xiong, Ilias Maglogiannis, Longxiang Gao, Manning Wang:
FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification. - Nunzio Alexandro Letizia, Nicola Novello, Andrea M. Tonello:
Mutual Information Estimation via f-Divergence and Data Derangements. - Federico Mora, Justin Wong, Haley Lepe, Sahil Bhatia, Karim Elmaaroufi, George Varghese, Joseph E. Gonzalez, Elizabeth Polgreen, Sanjit Seshia:
Synthetic Programming Elicitation for Text-to-Code in Very Low-Resource Programming and Formal Languages. - Konstantinos P. Panousis, Dino Ienco, Diego Marcos:
Coarse-to-Fine Concept Bottleneck Models. - Shuyang Jiang, Yusheng Liao, Ya Zhang, Yanfeng Wang, Yu Wang:
TAIA: Large Language Models are Out-of-Distribution Data Learners. - Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew M. Bean, Katerina Margatina, Rafael Mosquera Gómez, Juan Ciro, Max Bartolo, Adina Williams, He He, Bertie Vidgen, Scott Hale:
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models. - Jiacheng Ye, Shansan Gong, Liheng Chen, Lin Zheng, Jiahui Gao, Han Shi, Chuan Wu, Xin Jiang, Zhenguo Li, Wei Bi, Lingpeng Kong:
Diffusion of Thought: Chain-of-Thought Reasoning in Diffusion Language Models. - Pablo Diego-Simón, Stéphane d'Ascoli, Emmanuel Chemla, Yair Lakretz, Jean-Remi King:
A Polar coordinate system represents syntax in large language models. - Zhenzhi Wang, Jingbo Wang, Yixuan Li, Dahua Lin, Bo Dai:
InterControl: Zero-shot Human Interaction Generation by Controlling Every Joint. - Yuanshun Yao, Xiaojun Xu, Yang Liu:
Large Language Model Unlearning. - Jun-Hui Kim, Seong-Whan Lee:
Toward Approaches to Scalability in 3D Human Pose Estimation. - Yadong Qu, Yuxin Wang, Bangbang Zhou, Zixiao Wang, Hongtao Xie, Yongdong Zhang:
Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing. - Andrea Corsini, Angelo Porrello, Simone Calderara, Mauro Dell'Amico:
Self-Labeling the Job Shop Scheduling Problem. - Song Wu, Zhiyu Zhu, Junhui Hou, Guangming Shi, Jinjian Wu:
E-Motion: Future Motion Simulation via Event Sequence Diffusion. - Alessio Russo, Filippo Vannella:
Multi-Reward Best Policy Identification. - Rana Shahout, Michael Mitzenmacher:
SkipPredict: When to Invest in Predictions for Scheduling. - Alessandro Ragano, Jan Skoglund, Andrew Hines:
SCOREQ: Speech Quality Assessment with Contrastive Regression. - Subham S. Sahoo, Aaron Gokaslan, Christopher De Sa, Volodymyr Kuleshov:
Diffusion Models With Learned Adaptive Noise. - Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, Amirarsalan Rajabi, Aida Tayebi, Ivan Garibay, Ozlem O. Garibay:
Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium. - Qingyuan Zeng, Zhenzhong Wang, Yiu-ming Cheung, Min Jiang:
Ask, Attend, Attack: An Effective Decision-Based Black-Box Targeted Attack for Image-to-Text Models. - Huaiyuan Ying, Zijian Wu, Yihan Geng, Jiayu Wang, Dahua Lin, Kai Chen:
Lean Workbook: A large-scale Lean problem set formalized from natural language math problems. - Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins:
Tight Bounds for Learning RUMs from Small Slates. - Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou:
On the Computational Landscape of Replicable Learning. - Dongqi Cai, Shangguang Wang, Zeling Zhang, Felix Xiaozhu Lin, Mengwei Xu:
SILENCE: Protecting privacy in offloaded speech understanding on resource-constrained devices. - Shenghao Fu, Junkai Yan, Qize Yang, Xihan Wei, Xiaohua Xie, Wei-Shi Zheng:
Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models. - Jaeyoo Park, Jin Young Choi, Jeonghyung Park, Bohyung Han:
Hierarchical Visual Feature Aggregation for OCR-Free Document Understanding. - Bing Yang, Changsheng Quan, Yabo Wang, Pengyu Wang, Yujie Yang, Ying Fang, Nian Shao, Hui Bu, Xin Xu, Xiaofei Li:
RealMAN: A Real-Recorded and Annotated Microphone Array Dataset for Dynamic Speech Enhancement and Localization. - Rajat Modi, Yogesh S. Rawat:
Asynchronous Perception Machine for Efficient Test Time Training. - Zhenfeng Tu, Santiago Aranguri, Arthur Jacot:
Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes. - Ahmed Ben Yahmed, Clément Calauzènes, Vianney Perchet:
Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting. - Meriem Boubdir, Edward Kim, Beyza Ermis, Sara Hooker, Marzieh Fadaee:
Elo Uncovered: Robustness and Best Practices in Language Model Evaluation. - Jiacheng Miao, Qiongshi Lu:
Task-Agnostic Machine-Learning-Assisted Inference. - Chengquan Guo, Xun Liu, Chulin Xie, Andy Zhou, Yi Zeng, Zinan Lin, Dawn Song, Bo Li:
RedCode: Risky Code Execution and Generation Benchmark for Code Agents. - François Bertholom, Randal Douc, François Roueff:
Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families. - Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea:
Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching. - Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco:
Neuronal Competition Groups with Supervised STDP for Spike-Based Classification. - Shengsheng Lin, Weiwei Lin, Xinyi Hu, Wentai Wu, Ruichao Mo, Haocheng Zhong:
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns. - Peizhao Li, Junfeng He, Gang Li, Rachit Bhargava, Shaolei Shen, Nachiappan Valliappan, Youwei Liang, Hongxiang Gu, Venky Ramachandran, Golnaz Farhadi, Yang Li, Kai Kohlhoff, Vidhya Navalpakkam:
UniAR: A Unified model for predicting human Attention and Responses on visual content. - Ralph Peterson, Aramis Tanelus, Christopher Ick, Bartul Mimica, Niegil Francis Muttath Joseph, Violet Ivan, Aman Choudhri, Annegret Falkner, Mala Murthy, David M. Schneider, Dan Sanes, Alex Williams:
Vocal Call Locator Benchmark (VCL) for localizing rodent vocalizations from multi-channel audio. - Rwiddhi Chakraborty, Yinong Wang, Jialu Gao, Runkai Zheng, Cheng Zhang, Fernando De la Torre:
Visual Data Diagnosis and Debiasing with Concept Graphs. - Abhipsa Basu, Saswat Subhajyoti Mallick, R. Venkatesh Babu:
Mitigating Biases in Blackbox Feature Extractors for Image Classification Tasks. - Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado Philip van Hasselt, Razvan Pascanu, Will Dabney:
Normalization and effective learning rates in reinforcement learning. - Angéline Pouget, Lucas Beyer, Emanuele Bugliarello, Xiao Wang, Andreas Steiner, Xiaohua Zhai, Ibrahim M. Alabdulmohsin:
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models. - Xi Zhang, Xiaolin Wu:
Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression. - Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Ivan Rodkin, Dmitry Sorokin, Artyom Y. Sorokin, Mikhail Burtsev:
BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack. - Sijia Chen, Yibo Wang, Yi-Feng Wu, Qingguo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang:
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees. - Bozhou Zhang, Nan Song, Li Zhang:
DeMo: Decoupling Motion Forecasting into Directional Intentions and Dynamic States. - Dominik Hollidt, Paul Streli, Jiaxi Jiang, Yasaman Haghighi, Changlin Qian, Xintong Liu, Christian Holz:
EgoSim: An Egocentric Multi-view Simulator and Real Dataset for Body-worn Cameras during Motion and Activity. - Momin Haider, Ming Yin, Menglei Zhang, Arpit Gupta, Jing Zhu, Yu-Xiang Wang:
NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation. - Yubin Hu, Kairui Wen, Heng Zhou, Xiaoyang Guo, Yong-Jin Liu:
SS3DM: Benchmarking Street-View Surface Reconstruction with a Synthetic 3D Mesh Dataset. - Juno Kim, Tai Nakamaki, Taiji Suzuki:
Transformers are Minimax Optimal Nonparametric In-Context Learners. - Yura Perugachi-Diaz, Arwin Gansekoele, Sandjai Bhulai:
Robustly overfitting latents for flexible neural image compression. - Lujian Yao, Haitao Zhao, Zhongze Wang, Kaijie Zhao, Jingchao Peng:
CoSW: Conditional Sample Weighting for Smoke Segmentation with Label Noise. - Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev:
SPEAR: Exact Gradient Inversion of Batches in Federated Learning. - Ioannis Kalogeropoulos, Giorgos Bouritsas, Yannis Panagakis:
Scale Equivariant Graph Metanetworks. - Pouya M. Ghari, Alex M. Tseng, Gökcen Eraslan, Romain Lopez, Tommaso Biancalani, Gabriele Scalia, Ehsan Hajiramezanali:
GFlowNet Assisted Biological Sequence Editing. - Zixiang Chen, Huizhuo Yuan, Yongqian Li, Yiwen Kou, Junkai Zhang, Quanquan Gu:
Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time. - Cheonjun Park, Mincheol Park, Hyunchan Moon, Myung Kuk Yoon, Seokjin Go, Suhyun Kim, Won Woo Ro:
DEPrune: Depth-wise Separable Convolution Pruning for Maximizing GPU Parallelism. - Ruihan Wu, Siddhartha Datta, Yi Su, Dheeraj Baby, Yu-Xiang Wang, Kilian Q. Weinberger:
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation. - Jiongli Zhu, Su Feng, Boris Glavic, Babak Salimi:
Learning from Uncertain Data: From Possible Worlds to Possible Models. - Sapana Chaudhary, Ujwal Dinesha, Dileep Kalathil, Srinivas Shakkottai:
Risk-Averse Fine-tuning of Large Language Models. - Cheng-Kuang Wu, Zhi Rui Tam, Chieh-Yen Lin, Yun-Nung Chen, Hung-yi Lee:
StreamBench: Towards Benchmarking Continuous Improvement of Language Agents. - Yuedong Chen, Chuanxia Zheng, Haofei Xu, Bohan Zhuang, Andrea Vedaldi, Tat-Jen Cham, Jianfei Cai:
MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views. - Hyosoon Jang, Yunhui Jang, Minsu Kim, Jinkyoo Park, Sungsoo Ahn:
Pessimistic Backward Policy for GFlowNets. - Gui Ling, Ziyang Wang, Yuliang Yan, Qingwen Liu:
SlimGPT: Layer-wise Structured Pruning for Large Language Models. - Lars van der Laan, Ahmed M. Alaa:
Self-Calibrating Conformal Prediction. - Jian Hu, Jiayi Lin, Junchi Yan, Shaogang Gong:
Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation. - Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alexander Tong:
Trajectory Flow Matching with Applications to Clinical Time Series Modelling. - Guozhen Zhang, Chunxu Liu, Yutao Cui, Xiaotong Zhao, Kai Ma, Limin Wang:
VFIMamba: Video Frame Interpolation with State Space Models. - Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao:
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. - Rawal Khirodkar, Jyun-Ting Song, Jinkun Cao, Zhengyi Luo, Kris Kitani:
Harmony4D: A Video Dataset for In-The-Wild Close Human Interactions. - Dan Braun, Jordan Taylor, Nicholas Goldowsky-Dill, Lee Sharkey:
Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning. - Yunsong Wang, Tianxin Huang, Hanlin Chen, Gim Hee Lee:
FreeSplat: Generalizable 3D Gaussian Splatting Towards Free View Synthesis of Indoor Scenes. - Cédric Rommel, Victor Letzelter, Nermin Samet, Renaud Marlet, Matthieu Cord, Patrick Pérez, Eduardo Valle:
ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation. - Jinhui Ye, Xing Wang, Wenxiang Jiao, Junwei Liang, Hui Xiong:
Improving Gloss-free Sign Language Translation by Reducing Representation Density. - Zehong Wang, Zheyuan Zhang, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye:
GFT: Graph Foundation Model with Transferable Tree Vocabulary. - Pin-Yen Huang, Szu-Wei Fu, Yu Tsao:
RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier. - Xiyuan Zhang, Diyan Teng, Ranak Roy Chowdhury, Shuheng Li, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang:
UniMTS: Unified Pre-training for Motion Time Series. - Gongfan Fang, Xinyin Ma, Xinchao Wang:
Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising. - Alexander Kolesov, Petr Mokrov, Igor Udovichenko, Milena Gazdieva, Gudmund Pammer, Anastasis Kratsios, Evgeny Burnaev, Aleksandr Korotin:
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs. - Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
xLSTM: Extended Long Short-Term Memory. - Yifan Duan, Jian Zhao, pengcheng, Junyuan Mao, Hao Wu, Jingyu Xu, Shilong Wang, Caoyuan Ma, Kai Wang, Kun Wang, Xuelong Li:
Causal Deciphering and Inpainting in Spatio-Temporal Dynamics via Diffusion Model. - Fangrui Zhu, Jianwei Yang, Huaizu Jiang:
Towards Flexible Visual Relationship Segmentation. - Ruofeng Yang, Zhijie Wang, Bo Jiang, Shuai Li:
Leveraging Drift to Improve Sample Complexity of Variance Exploding Diffusion Models. - Ruisheng Cao, Fangyu Lei, Haoyuan Wu, Jixuan Chen, Yeqiao Fu, Hongcheng Gao, Xinzhuang Xiong, Hanchong Zhang, Wenjing Hu, Yuchen Mao, Tianbao Xie, Hongshen Xu, Danyang Zhang, Sida I. Wang, Ruoxi Sun, Pengcheng Yin, Caiming Xiong, Ansong Ni, Qian Liu, Victor Zhong, Lu Chen, Kai Yu, Tao Yu:
Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows? - Jun Chen, Hong Chen, Bin Gu:
How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization? - Rabiul Awal, Saba Ahmadi, Le Zhang, Aishwarya Agrawal:
VisMin: Visual Minimal-Change Understanding. - Maohao Shen, Jongha Jon Ryu, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell:
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage? - Joanna Waczynska, Piotr Borycki, Joanna Kaleta, Slawomir Konrad Tadeja, Przemyslaw Spurek:
D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup. - Kirill Brilliantov, Amauri H. Souza, Vikas Garg:
Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond. - Sharang M. Sriramu, Rochelle Barsz, Elizabeth Polito, Aaron B. Wagner:
Fast Channel Simulation via Error-Correcting Codes. - Christopher Williams, Andrew Campbell, Arnaud Doucet, Saifuddin Syed:
Score-Optimal Diffusion Schedules. - Ao Wang, Hui Chen, Lihao Liu, Kai Chen, Zijia Lin, Jungong Han, Guiguang Ding:
YOLOv10: Real-Time End-to-End Object Detection. - Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein:
Transformers Can Do Arithmetic with the Right Embeddings. - Shayne Longpre, Robert Mahari, Ariel Lee, Campbell Lund, Hamidah Oderinwale, William Brannon, Nayan Saxena, Naana Obeng-Marnu, Tobin South, Cole Hunter, Kevin Klyman, Christopher Klamm, Hailey Schoelkopf, Nikhil Singh, Manuel Cherep, Ahmad Anis, An Dinh, Caroline Shamiso Chitongo, Da Yin, Damien Sileo, Deividas Mataciunas, Diganta Misra, Emad A. Alghamdi, Enrico Shippole, Jianguo Zhang, Joanna Materzynska, Kun Qian, Kushagra Tiwary, Lester James V. Miranda, Manan Dey, Minnie Liang, Mohammed Hamdy, Niklas Muennighoff, Seonghyeon Ye, Seungone Kim, Shrestha Mohanty, Vipul Gupta, Vivek Sharma, Minh Chien Vu, Xuhui Zhou, Yizhi Li, Caiming Xiong, Luis Villa, Stella Biderman, Hanlin Li, Daphne Ippolito, Sara Hooker, Jad Kabbara, Alex Pentland:
Consent in Crisis: The Rapid Decline of the AI Data Commons. - Qi Ju, Falin Hei, Ting Feng, Dengbing Yi, Zhemei Fang, Yunfeng Luo:
Accelerating Nash Equilibrium Convergence in Monte Carlo Settings Through Counterfactual Value Based Fictitious Play. - Renjie Pi, Jianshu Zhang, Jipeng Zhang, Rui Pan, Zhekai Chen, Tong Zhang:
Image Textualization: An Automatic Framework for Generating Rich and Detailed Image Descriptions. - Khai Nguyen, Nhat Ho:
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions. - Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang:
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL. - Rui Liu, Wenguan Wang, Yi Yang:
Vision-Language Navigation with Energy-Based Policy. - Qinghua Liu, John Paparrizos:
The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark. - Tyler Sam, Yudong Chen, Christina Lee Yu:
The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure. - Rohit Jena, Deeksha Sethi, Pratik Chaudhari, James C. Gee:
Deep Learning in Medical Image Registration: Magic or Mirage? - Yunbum Kook, Santosh S. Vempala, Matthew Shunshi Zhang:
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies. - Yiming Li, Zehong Wang, Yue Wang, Zhiding Yu, Zan Gojcic, Marco Pavone, Chen Feng, José M. Álvarez:
Memorize What Matters: Emergent Scene Decomposition from Multitraverse. - Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony L. Caterini:
Retrieval & Fine-Tuning for In-Context Tabular Models. - Florian Kalinke, Zoltán Szabó:
The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels. - Tao Dai, Beiliang Wu, Peiyuan Liu, Naiqi Li, Xue Yuerong, Shu-Tao Xia, Zexuan Zhu:
DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting. - Quoc Phong Nguyen, Sunil Gupta, Svetha Venkatesh, Bryan Kian Hsiang Low, Patrick Jaillet:
Active Set Ordering. - Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugène Ndiaye, Jonathan Niles-Weed, Marco Cuturi:
Learning Elastic Costs to Shape Monge Displacements. - Qinbo Bai, Washim Uddin Mondal, Vaneet Aggarwal:
Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm. - Georgios Mentzelopoulos, Evangelos Chatzipantazis, Ashwin G. Ramayya, Michelle J. Hedlund, Vivek P. Buch, Kostas Daniilidis, Konrad P. Kording, Flavia Vitale:
Neural decoding from stereotactic EEG: accounting for electrode variability across subjects. - Jisong Kim, Minjae Seong, Jun Won Choi:
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object Detection. - Omar Montasser, Han Shao, Emmanuel Abbe:
Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization. - Xiang Zhang, Bingxin Ke, Hayko Riemenschneider, Nando Metzger, Anton Obukhov, Markus Gross, Konrad Schindler, Christopher Schroers:
BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation. - Jonas Guan, Shon Eduard Verch, Claas Voelcker, Ethan C. Jackson, Nicolas Papernot, William A. Cunningham:
Temporal-Difference Learning Using Distributed Error Signals. - Zichun Yu, Spandan Das, Chenyan Xiong:
MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models. - Yanfei Zhou, Matteo Sesia:
Conformal Classification with Equalized Coverage for Adaptively Selected Groups. - Emily Jin, Zhuoyi Huang, Jan-Philipp Fränken, Weiyu Liu, Hannah Cha, Erik Brockbank, Sarah Wu, Ruohan Zhang, Jiajun Wu, Tobias Gerstenberg:
MARPLE: A Benchmark for Long-Horizon Inference. - Zejia Weng, Xitong Yang, Zhen Xing, Zuxuan Wu, Yu-Gang Jiang:
GenRec: Unifying Video Generation and Recognition with Diffusion Models. - Tong Mu, Alec Helyar, Johannes Heidecke, Joshua Achiam, Andrea Vallone, Ian Kivlichan, Molly Lin, Alex Beutel, John Schulman, Lilian Weng:
Rule Based Rewards for Language Model Safety. - Pin Chen, Luoxuan Peng, Rui Jiao, Qing Mo, Zhen Wang, Wenbing Huang, Yang Liu, Yutong Lu:
Learning Superconductivity from Ordered and Disordered Material Structures. - Yixin Chen, Ankur Nath, Chunli Peng, Alan Kuhnle:
Discretely beyond 1/e: Guided Combinatorial Algortihms for Submodular Maximization. - Yifei Shen, Xinyang Jiang, Yifan Yang, Yezhen Wang, Dongqi Han, Dongsheng Li:
Understanding and Improving Training-free Loss-based Diffusion Guidance. - Joongkyu Lee, Min-hwan Oh:
Nearly Minimax Optimal Regret for Multinomial Logistic Bandit. - Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu:
Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits. - Vivien Cabannes, Charles Arnal, Wassim Bouaziz, Xingyu Yang, François Charton, Julia Kempe:
Iteration Head: A Mechanistic Study of Chain-of-Thought. - Alexander Levis, Gabriel Loewinger, Francisco Pereira:
Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects. - Kai Liu, Zhihang Fu, Sheng Jin, Chao Chen, Ze Chen, Rongxin Jiang, Fan Zhou, Yaowu Chen, Jieping Ye:
Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution. - Seokin Seo, Byung-Jun Lee, Jongmin Lee, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim:
Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction. - Léopold Maillard, Nicolas Sereyjol-Garros, Tom Durand, Maks Ovsjanikov:
DeBaRA: Denoising-Based 3D Room Arrangement Generation. - Maximilian Li, Lucas Janson:
Optimal ablation for interpretability. - Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
Bridging Geometric States via Geometric Diffusion Bridge. - Haixin Zhong, Mingyi Huang, Wei Dai, Haoyu Wang, Anna Roe, Yuguo Yu:
Visual Pinwheel Centers Act as Geometric Saliency Detectors. - Wei Li, Lujun Li, Mark Lee, Shengjie Sun:
Adaptive Layer Sparsity for Large Language Models via Activation Correlation Assessment. - Xingyu Cui, Huanjing Yue, Song Li, Xiangjun Yin, Yusen Hou, Yun Meng, Kai Zou, Xiaolong Hu, Jingyu Yang:
Virtual Scanning: Unsupervised Non-line-of-sight Imaging from Irregularly Undersampled Transients. - R. Kenny Jones, Renhao Zhang, Aditya Ganeshan, Daniel Ritchie:
Learning to Edit Visual Programs with Self-Supervision. - Weikang Wan, Ziyu Wang, Yufei Wang, Zackory Erickson, David Held:
DiffTORI: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation Learning. - Daolang Huang, Yujia Guo, Luigi Acerbi, Samuel Kaski:
Amortized Bayesian Experimental Design for Decision-Making. - Xin Cheng, Xun Wang, Xingxing Zhang, Tao Ge, Si-Qing Chen, Furu Wei, Huishuai Zhang, Dongyan Zhao:
xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token. - Anna Arutyunova, Jan Eube, Heiko Röglin, Melanie Schmidt, Sarah Sturm, Julian Wargalla:
Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering. - Haotong Du, Quanming Yao, Juzheng Zhang, Yang Liu, Zhen Wang:
Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction. - James Requeima, John Bronskill, Dami Choi, Richard E. Turner, David Kristjanson Duvenaud:
LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language. - Haoran Li, Zhennan Jiang, Yuhui Chen, Dongbin Zhao:
Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization. - Yufang Hou, Alessandra Pascale, Javier Carnerero-Cano, Tigran T. Tchrakian, Radu Marinescu, Elizabeth Daly, Inkit Padhi, Prasanna Sattigeri:
WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia. - Stefan K. Nielsen, Laziz U. Abdullaev, Rachel S. Y. Teo, Tan Nguyen:
Elliptical Attention. - Mingxiang Liao, Hannan Lu, Qixiang Ye, Wangmeng Zuo, Fang Wan, Tianyu Wang, Yuzhong Zhao, Jingdong Wang, Xinyu Zhang:
Evaluation of Text-to-Video Generation Models: A Dynamics Perspective. - Jiaojiao Zhang, Jiang Hu, Anthony Man-Cho So, Mikael Johansson:
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data. - Matthew Chan, Maria Molina, Chris Metzler:
Estimating Epistemic and Aleatoric Uncertainty with a Single Model. - Zefan Qu, Ke Xu, Gerhard P. Hancke, Rynson W. H. Lau:
LuSh-NeRF: Lighting up and Sharpening NeRFs for Low-light Scenes. - Ruosen Li, Ruochen Li, Barry Wang, Xinya Du:
IQA-EVAL: Automatic Evaluation of Human-Model Interactive Question Answering. - Shiwei Wu, Joya Chen, Kevin Qinghong Lin, Qimeng Wang, Yan Gao, Qianli Xu, Tong Xu, Yao Hu, Enhong Chen, Mike Zheng Shou:
VideoLLM-MoD: Efficient Video-Language Streaming with Mixture-of-Depths Vision Computation. - Adrienne Tuynman, Rémy Degenne, Emilie Kaufmann:
Finding good policies in average-reward Markov Decision Processes without prior knowledge. - Junru Chen, Tianyu Cao, Jing Xu, Jiahe Li, Zhilong Chen, Tao Xiao, Yang Yang:
Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification. - Roman Bushuiev, Anton Bushuiev, Niek F. de Jonge, Adamo Young, Fleming Kretschmer, Raman Samusevich, Janne Heirman, Fei Wang, Luke Zhang, Kai Dührkop, Marcus Ludwig, Nils A. Haupt, Apurva Kalia, Corinna Brungs, Robin Schmid, Russell Greiner, Bo Wang, David S. Wishart, Liping Liu, Juho Rousu, Wout Bittremieux, Hannes Rost, Tytus D. Mak, Soha Hassoun, Florian Huber, Justin J. J. van der Hooft, Michael A. Stravs, Sebastian Böcker, Josef Sivic, Tomás Pluskal:
MassSpecGym: A benchmark for the discovery and identification of molecules. - Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai:
Diffusion Spectral Representation for Reinforcement Learning. - Ilan Reuven Cohen, Alon Eden, Talya Eden, Arsen Vasilyan:
Plant-and-Steal: Truthful Fair Allocations via Predictions. - Zhichao Hou, Ruiqi Feng, Tyler Derr, Xiaorui Liu:
Robust Graph Neural Networks via Unbiased Aggregation. - Yiran Liu, Ke Yang, Zehan Qi, Xiao Liu, Yang Yu, Cheng Xiang Zhai:
Bias and Volatility: A Statistical Framework for Evaluating Large Language Model's Stereotypes and the Associated Generation Inconsistency. - Rotem Ben Zion, Boaz Carmeli, Orr Paradise, Yonatan Belinkov:
Semantics and Spatiality of Emergent Communication. - Rui Jiao, Xiangzhe Kong, Wenbing Huang, Yang Liu:
3D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization. - Changyi Xiao, Yixin Cao:
Knowledge Graph Completion by Intermediate Variables Regularization. - Ayush Jain, Andrea Montanari, Eren Sasoglu:
Scaling laws for learning with real and surrogate data. - Kaihang Pan, Zhaoyu Fan, Juncheng Li, Qifan Yu, Hao Fei, Siliang Tang, Richang Hong, Hanwang Zhang, Qianru Sun:
Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration. - Yupeng Zhou, Daquan Zhou, Ming-Ming Cheng, Jiashi Feng, Qibin Hou:
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation. - Andrew C. Li, Zizhao Chen, Toryn Q. Klassen, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith:
Reward Machines for Deep RL in Noisy and Uncertain Environments. - Junfeng Zuo, Ying Nian Wu, Si Wu, Wenhao Zhang:
The motion planning neural circuit in goal-directed navigation as Lie group operator search. - Xinyao Yu, Sixian Zhang, Xinhang Song, Xiaorong Qin, Shuqiang Jiang:
Trajectory Diffusion for ObjectGoal Navigation. - Junha Hyung, Susung Hong, Sungwon Hwang, Jaeseong Lee, Jaegul Choo, Jin-Hwa Kim:
Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting. - Ioannis Zachos, Mark Girolami, Theodoros Damoulas:
Generating Origin-Destination Matrices in Neural Spatial Interaction Models. - Peter Holderrieth, Yilun Xu, Tommi S. Jaakkola:
Hamiltonian Score Matching and Generative Flows. - Haixu Wu, Huakun Luo, Yuezhou Ma, Jianmin Wang, Mingsheng Long:
RoPINN: Region Optimized Physics-Informed Neural Networks. - Navami Kairanda, Marc Habermann, Christian Theobalt, Vladislav Golyanik:
NeuralClothSim: Neural Deformation Fields Meet the Thin Shell Theory. - Xuehui Yu, Mhairi Dunion, Xin Li, Stefano V. Albrecht:
Skill-aware Mutual Information Optimisation for Zero-shot Generalisation in Reinforcement Learning. - Chengtao Jian, Kai Yang, Yang Jiao:
Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization. - Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Sixiang Chen, Tian Ye, Renjing Pei, Kaiwen Zhou, Fenglong Song, Lei Zhu:
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models. - Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini:
How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval. - William Overman, Jacqueline Jil Vallon, Mohsen Bayati:
Aligning Model Properties via Conformal Risk Control. - Graham Todd, Alexander Padula, Matthew Stephenson, Éric Piette, Dennis J. N. J. Soemers, Julian Togelius:
GAVEL: Generating Games via Evolution and Language Models. - Yuxin Du, Fan Bai, Tiejun Huang, Bo Zhao:
SegVol: Universal and Interactive Volumetric Medical Image Segmentation. - Anna Varbella, Kenza Amara, Blazhe Gjorgiev, Mennatallah El-Assady, Giovanni Sansavini:
PowerGraph: A power grid benchmark dataset for graph neural networks. - Zebang Cheng, Zhi-Qi Cheng, Jun-Yan He, Kai Wang, Yuxiang Lin, Zheng Lian, Xiaojiang Peng, Alexander G. Hauptmann:
Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning. - Hanwen Liang, Yuyang Yin, Dejia Xu, Hanxue Liang, Zhangyang Wang, Konstantinos N. Plataniotis, Yao Zhao, Yunchao Wei:
Diffusion4D: Fast Spatial-temporal Consistent 4D generation via Video Diffusion Models. - Sukjun Hwang, Aakash Sunil Lahoti, Ratish Puduppully, Tri Dao, Albert Gu:
Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers. - Akhil Agnihotri, Rahul Jain, Deepak Ramachandran, Sahil Singla:
e-COP : Episodic Constrained Optimization of Policies. - Simon Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Peter Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine:
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. - Changli Wu, Qi Chen, Jiayi Ji, Haowei Wang, Yiwei Ma, You Huang, Gen Luo, Hao Fei, Xiaoshuai Sun, Rongrong Ji:
RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation. - Yuanhao Zhai, Kevin Lin, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Chung-Ching Lin, David S. Doermann, Junsong Yuan, Lijuan Wang:
Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation. - Yiqi Zhong, Luming Liang, Bohan Tang, Ilya Zharkov, Ulrich Neumann:
Motion Graph Unleashed: A Novel Approach to Video Prediction. - Shani Goren, Ido Galil, Ran El-Yaniv:
Hierarchical Selective Classification. - António Farinhas, Haau-Sing Li, André Martins:
Reranking Laws for Language Generation: A Communication-Theoretic Perspective. - Rui Ye, Rui Ge, Xinyu Zhu, Jingyi Chai, Yaxin Du, Yang Liu, Yanfeng Wang, Siheng Chen:
FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models. - Jingjing Ren, Wenbo Li, Haoyu Chen, Renjing Pei, Bin Shao, Yong Guo, Long Peng, Fenglong Song, Lei Zhu:
UltraPixel: Advancing Ultra High-Resolution Image Synthesis to New Peaks. - Debidatta Dwibedi, Vidhi Jain, Jonathan Tompson, Andrew Zisserman, Yusuf Aytar:
FlexCap: Describe Anything in Images in Controllable Detail. - Qian Shao, Jiangrui Kang, Qiyuan Chen, Zepeng Li, Hongxia Xu, Yiwen Cao, Jiajuan Liang, Jian Wu:
Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection. - Yushan Zhang, Bastian Wandt, Maria Magnusson, Michael Felsberg:
DiffSF: Diffusion Models for Scene Flow Estimation. - Felix Benning, Leif Döring:
Random Function Descent. - Leon Kellerhals, Jannik Peters:
Proportional Fairness in Clustering: A Social Choice Perspective. - Ruinan Jin, Zikang Xu, Yuan Zhong, Qingsong Yao, Qi Dou, S. Kevin Zhou, Xiaoxiao Li:
FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models. - Nayeon Kim, Hongje Seong, Daehyun Ji, Sujin Jang:
Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation. - Jiayi Shen, Qi Wang, Zehao Xiao, Nanne van Noord, Marcel Worring:
GO4Align: Group Optimization for Multi-Task Alignment. - Hongliang Wei, Xingtao Wang, Xianqi Zhang, Xiaopeng Fan, Debin Zhao:
Toward a Stable, Fair, and Comprehensive Evaluation of Object Hallucination in Large Vision-Language Models. - Pietro Novelli, Marco Pratticò, Massimiliano Pontil, Carlo Ciliberto:
Operator World Models for Reinforcement Learning. - Roshni G. Iyer, Yewen Wang, Wei Wang, Yizhou Sun:
Non-Euclidean Mixture Model for Social Network Embedding. - Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson, William W. Cohen:
Stratified Prediction-Powered Inference for Effective Hybrid Evaluation of Language Models. - Ahmed Said Donmez, Yuksel Arslantas, Muhammed Omer Sayin:
Team-Fictitious Play for Reaching Team-Nash Equilibrium in Multi-team Games. - Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Qingwei Lin, Jian-Guang Lou, Shifeng Chen, Yansong Tang, Weizhu Chen:
WizardArena: Post-training Large Language Models via Simulated Offline Chatbot Arena. - Noah Golowich, Elad Hazan, Zhou Lu, Dhruv Rohatgi, Y. Jennifer Sun:
Online Control in Population Dynamics. - Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer:
Linear Causal Representation Learning from Unknown Multi-node Interventions. - Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani:
Bayesian Strategic Classification. - Zixuan Chen, Ze Ji, Jing Huo, Yang Gao:
SCaR: Refining Skill Chaining for Long-Horizon Robotic Manipulation via Dual Regularization. - Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, Rada Mihalcea:
Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents. - Dayal Singh Kalra, Maissam Barkeshli:
Why Warmup the Learning Rate? Underlying Mechanisms and Improvements. - Tianshi Xu, Lemeng Wu, Runsheng Wang, Meng Li:
PrivCirNet: Efficient Private Inference via Block Circulant Transformation. - Caroline Wang, Arrasy Rahman, Ishan Durugkar, Elad Liebman, Peter Stone:
N-agent Ad Hoc Teamwork. - Yuxuan Qiao, Haodong Duan, Xinyu Fang, Junming Yang, Lin Chen, Songyang Zhang, Jiaqi Wang, Dahua Lin, Kai Chen:
Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs. - Qitao Zhao, Shubham Tulsiani:
Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis. - Parsa Moradi, Behrooz Tahmasebi, Mohammad Ali Maddah-Ali:
Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework. - Yilang Zhang, Alireza Sadeghi, Georgios B. Giannakis:
Meta-Learning Universal Priors Using Non-Injective Change of Variables. - Ethan Rathbun, Christopher Amato, Alina Oprea:
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents. - Qi Shen, Junchang Xin, Bing Tian Dai, Shudi Zhang, Zhiqiong Wang:
Robust Sleep Staging over Incomplete Multimodal Physiological Signals via Contrastive Imagination. - Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Hao Wang:
Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective. - Hengyuan Ma, Wenlian Lu, Jianfeng Feng:
Efficient Combinatorial Optimization via Heat Diffusion. - Sukmin Yun, Haokun Lin, Rusiru Thushara, Mohammad Qazim Bhat, Yongxin Wang, Zutao Jiang, Mingkai Deng, Jinhong Wang, Tianhua Tao, Junbo Li, Haonan Li, Preslav Nakov, Timothy Baldwin, Zhengzhong Liu, Eric P. Xing, Xiaodan Liang, Zhiqiang Shen:
Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs. - Hilal Asi, Tomer Koren, Daogao Liu, Kunal Talwar:
Private Online Learning via Lazy Algorithms. - Chen Jia:
Adversarial Moment-Matching Distillation of Large Language Models. - Dayou Yu, Minghao Li, Weishi Shi, Qi Yu:
Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity. - Yiyang Guo, Ruizhe Li, Mude Hui, Hanzhong Guo, Chen Zhang, Chuangjian Cai, Le Wan, Shangfei Wang:
FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space. - Farzaneh Askari, Lingjuan Lyu, Vivek Sharma:
DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release. - Haoxuan Qu, Zhuoling Li, Hossein Rahmani, Yujun Cai, Jun Liu:
DisC-GS: Discontinuity-aware Gaussian Splatting. - Ming Zhong, Fang Lyu, Lulin Wang, Hongna Geng, Lei Qiu, Huimin Cui, Xiaobing Feng:
ComBack: A Versatile Dataset for Enhancing Compiler Backend Development Efficiency. - Ouail Kitouni, Niklas Nolte, Adina Williams, Michael Rabbat, Diane Bouchacourt, Mark Ibrahim:
The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More. - Shiyue Zhang, Longlin Yu, Ziheng Cheng, Cheng Zhang:
Functional Gradient Flows for Constrained Sampling. - Yanjiang Guo, Yucheng Hu, Jianke Zhang, Yen-Jen Wang, Xiaoyu Chen, Chaochao Lu, Jianyu Chen:
Prediction with Action: Visual Policy Learning via Joint Denoising Process. - Jiefeng Ma, Yan Wang, Chenyu Liu, Jun Du, Yu Hu, Zhenrong Zhang, Pengfei Hu, Qing Wang, Jianshu Zhang:
SRFUND: A Multi-Granularity Hierarchical Structure Reconstruction Benchmark in Form Understanding. - Yinghui Li, Qingyu Zhou, Yuanzhen Luo, Shirong Ma, Yangning Li, Hai-Tao Zheng, Xuming Hu, Philip S. Yu:
When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models. - Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen:
Stochastic Optimal Control Matching. - Paulius Rauba, Nabeel Seedat, Max Ruiz Luyten, Mihaela van der Schaar:
Context-Aware Testing: A New Paradigm for Model Testing with Large Language Models. - Liyuan Zhang, Le Hui, Qi Liu, Bo Li, Yuchao Dai:
3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration. - Laurynas Karazija, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
Learning Segmentation from Point Trajectories. - Yujin Wang, Tianyi Xu, Zhang Fan, Tianfan Xue, Jinwei Gu:
AdaptiveISP: Learning an Adaptive Image Signal Processor for Object Detection. - Zian Su, Xiangzhe Xu, Ziyang Huang, Kaiyuan Zhang, Xiangyu Zhang:
Source Code Foundation Models are Transferable Binary Analysis Knowledge Bases. - Joshua R. Loftus, Lucius Bynum, Sakina Hansen:
Causal Dependence Plots. - Ziyao Zeng, Yangchao Wu, Hyoungseob Park, Daniel Wang, Fengyu Yang, Stefano Soatto, Dong Lao, Byung-Woo Hong, Alex Wong:
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions. - Tianyi Zhang, Jonah Yi, Bowen Yao, Zhaozhuo Xu, Anshumali Shrivastava:
NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention. - Aditya Bhaskara, Agastya Vibhuti Jha, Michael Kapralov, Naren Manoj, Davide Mazzali, Weronika Wrzos-Kaminska:
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models. - Dario Fenoglio, Gabriele Dominici, Pietro Barbiero, Alberto Tonda, Martin Gjoreski, Marc Langheinrich:
Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning. - Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula, Vishal M. Patel:
Federated Black-Box Adaptation for Semantic Segmentation. - Paul Soulos, Henry Conklin, Mattia Opper, Paul Smolensky, Jianfeng Gao, Roland Fernandez:
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations. - Ibrahim M. Alabdulmohsin, Vinh Q. Tran, Mostafa Dehghani:
Fractal Patterns May Illuminate the Success of Next-Token Prediction. - Ben Shaw, Abram Magner, Kevin R. Moon:
Symmetry Discovery Beyond Affine Transformations. - Kevin Yu, Jihye Roh, Ziang Li, Wenhao Gao, Runzhong Wang, Connor W. Coley:
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search. - Chen Yeh, You-Ming Chang, Wei-Chen Chiu, Ning Yu:
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition. - Andrew Bennett, Nathan Kallus, Miruna Oprescu, Wen Sun, Kaiwen Wang:
Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes. - Yiwen Kou, Zixiang Chen, Quanquan Gu, Sham M. Kakade:
Matching the Statistical Query Lower Bound for k-Sparse Parity Problems with Sign Stochastic Gradient Descent. - Michal Nauman, Mateusz Ostaszewski, Krzysztof Jankowski, Piotr Milos, Marek Cygan:
Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control. - Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, Xiangnan He:
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation. - Ivi Chatzi, Eleni Straitouri, Suhas Thejaswi, Manuel Rodriguez:
Prediction-Powered Ranking of Large Language Models. - Renze Chen, Zhuofeng Wang, Beiquan Cao, Tong Wu, Size Zheng, Xiuhong Li, Xuechao Wei, Shengen Yan, Meng Li, Yun Liang:
ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction. - Michael Shalyt, Uri Seligmann, Itay Beit Halachmi, Ofir David, Rotem Elimelech, Ido Kaminer:
Unsupervised Discovery of Formulas for Mathematical Constants. - Adam Block, Mark Bun, Rathin Desai, Abhishek Shetty, Zhiwei Steven Wu:
Oracle-Efficient Differentially Private Learning with Public Data. - Hailiang Zhao, Xueyan Tang, Peng Chen, Shuiguang Deng:
Learning-Augmented Algorithms for the Bahncard Problem. - Jiaxian Yan, Zaixi Zhang, Jintao Zhu, Kai Zhang, Jianfeng Pei, Qi Liu:
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking. - Lijia Yu, Xiao-Shan Gao, Lijun Zhang, Yibo Miao:
Generalizablity of Memorization Neural Network. - Jingru Jia, Zehua Yuan, Junhao Pan, Paul McNamara, Deming Chen:
Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context. - Amelia Jiménez-Sánchez, Natalia Rozalia Avlona, Dovile Juodelyte, Théo Sourget, Caroline Vang-Larsen, Anna Rogers, Hubert Dariusz Zajac, Veronika Cheplygina:
Copycats: the many lives of a publicly available medical imaging dataset. - Junghyuk Yeom, Yonghyeon Jo, Jeongmo Kim, Sanghyeon Lee, Seungyul Han:
Exclusively Penalized Q-learning for Offline Reinforcement Learning. - Declan Campbell, Sunayana Rane, Tyler Giallanza, Nicolò De Sabbata, Kia Ghods, Amogh Joshi, Alexander Ku, Steven Frankland, Tom Griffiths, Jonathan D. Cohen, Taylor W. Webb:
Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem. - Praneeth Kacham, David P. Woodruff:
Approximating the Top Eigenvector in Random Order Streams. - Shen Yuan, Haotian Liu, Hongteng Xu:
Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation. - Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E. Gonzalez, Bin Cui:
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models. - Mengyu Zheng, Hanting Chen, Tianyu Guo, Chong Zhu, Binfan Zheng, Chang Xu, Yunhe Wang:
Enhancing Large Language Models through Adaptive Tokenizers. - Zirui Wang, Mengzhou Xia, Luxi He, Howard Chen, Yitao Liu, Richard Zhu, Kaiqu Liang, Xindi Wu, Haotian Liu, Sadhika Malladi, Alexis Chevalier, Sanjeev Arora, Danqi Chen:
CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs. - Xin Chen, Anderson Ye Zhang:
Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures. - Lidong Guo, Xuefei Ning, Yonggan Fu, Tianchen Zhao, Zhuoliang Kang, Jincheng Yu, Yingyan (Celine) Lin, Yu Wang:
Rad-NeRF: Ray-decoupled Training of Neural Radiance Field. - Linglan Zhao, Xuerui Zhang, Ke Yan, Shouhong Ding, Weiran Huang:
SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained Models. - Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart A. Silling:
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery. - Atsushi Nitanda:
Improved Particle Approximation Error for Mean Field Neural Networks. - Zhe Tao, Aditya V. Thakur:
Provable Editing of Deep Neural Networks using Parametric Linear Relaxation. - Arthur Juliani, Jordan T. Ash:
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning. - Dehao Zhang, Shuai Wang, Ammar Belatreche, Wenjie Wei, Yichen Xiao, Haorui Zheng, Zijian Zhou, Malu Zhang, Yang Yang:
Spike-based Neuromorphic Model for Sound Source Localization. - Changlong Wu, Ananth Grama, Wojciech Szpankowski:
Information-theoretic Limits of Online Classification with Noisy Labels. - Alexander C. Li, Yuandong Tian, Beidi Chen, Deepak Pathak, Xinlei Chen:
On the Surprising Effectiveness of Attention Transfer for Vision Transformers. - Haifeng Huang, Yilun Chen, Zehan Wang, Rongjie Huang, Runsen Xu, Tai Wang, Luping Liu, Xize Cheng, Yang Zhao, Jiangmiao Pang, Zhou Zhao:
Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers. - Biao Zhang, Garrett Tanzer, Orhan Firat:
Scaling Sign Language Translation. - Wei Wu, Xiaoxin Feng, Ziyan Gao, Yuheng Kan:
SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction. - Jiachen Liang, Ruibing Hou, Minyang Hu, Hong Chang, Shiguang Shan, Xilin Chen:
UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language Models. - Scott Pesme, Radu-Alexandru Dragomir, Nicolas Flammarion:
Implicit Bias of Mirror Flow on Separable Data. - Ronglong Fang, Yuesheng Xu:
Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning. - Chaofan Tao, Qian Liu, Longxu Dou, Niklas Muennighoff, Zhongwei Wan, Ping Luo, Min Lin, Ngai Wong:
Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies. - Dongbin Kim, Jinseong Park, Jaewook Lee, Hoki Kim:
Are Self-Attentions Effective for Time Series Forecasting? - Ike Obi, Rohan Pant, Srishti Shekhar Agrawal, Maham Ghazanfar, Aaron Basiletti:
Value Imprint: A Technique for Auditing the Human Values Embedded in RLHF Datasets. - Sophie Greenwood, Sudalakshmee Chiniah, Nikhil Garg:
User-item fairness tradeoffs in recommendations. - Teng Xiao, Yige Yuan, Huaisheng Zhu, Mingxiao Li, Vasant G. Honavar:
Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment. - Jihao Qiu, Yuan Zhang, Xi Tang, Lingxi Xie, Tianren Ma, Pengyu Yan, David S. Doermann, Qixiang Ye, Yunjie Tian:
Artemis: Towards Referential Understanding in Complex Videos. - Xiaoyun Xu, Zhuoran Liu, Stefanos Koffas, Shujian Yu, Stjepan Picek:
BAN: Detecting Backdoors Activated by Adversarial Neuron Noise. - Peter Halmos, Xinhao Liu, Julian Gold, Benjamin J. Raphael:
Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling. - Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo:
FIDE: Frequency-Inflated Conditional Diffusion Model for Extreme-Aware Time Series Generation. - Sandika Biswas, Qianyi Wu, Biplab Banerjee, Hamid Rezatofighi:
TFS-NeRF: Template-Free NeRF for Semantic 3D Reconstruction of Dynamic Scene. - Ming Chen, Jie Chun, Shang Xiang, Luona Wei, Yonghao Du, Qian Wan, Yuning Chen, Yingwu Chen:
Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way. - Haohong Lin, Wenhao Ding, Jian Chen, Laixi Shi, Jiacheng Zhu, Bo Li, Ding Zhao:
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning. - Changyuan Wang, Ziwei Wang, Xiuwei Xu, Yansong Tang, Jie Zhou, Jiwen Lu:
Q-VLM: Post-training Quantization for Large Vision-Language Models. - Jincheng Zhong, Xingzhuo Guo, Jiaxiang Dong, Mingsheng Long:
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting. - Alex Oesterling, Claudio Mayrink Verdun, Alex Glynn, Carol Xuan Long, Lucas Monteiro Paes, Sajani Vithana, Martina Cardone, Flávio P. Calmon:
Multi-Group Proportional Representation in Retrieval. - Junsoo Oh, Chulhee Yun:
Provable Benefit of Cutout and CutMix for Feature Learning. - Siyuan Zhang, Linbo Xie:
A PID Controller Approach for Adaptive Probability-dependent Gradient Decay in Model Calibration. - Wangbo Zhao, Jiasheng Tang, Yizeng Han, Yibing Song, Kai Wang, Gao Huang, Fan Wang, Yang You:
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation. - Brandon Victor, Mathilde Letard, Peter Naylor, Karim Douch, Nicolas Longépé, Zhen He, Patrick Ebel:
Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting. - John J. Cherian, Isaac Gibbs, Emmanuel J. Candès:
Large language model validity via enhanced conformal prediction methods. - Shuofei Qiao, Runnan Fang, Ningyu Zhang, Yuqi Zhu, Xiang Chen, Shumin Deng, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen:
Agent Planning with World Knowledge Model. - Zhihui Xie, Jizhou Guo, Tong Yu, Shuai Li:
Calibrating Reasoning in Language Models with Internal Consistency. - Antonin Joly, Nicolas Keriven:
Graph Coarsening with Message-Passing Guarantees. - Mingli Zhu, Siyuan Liang, Baoyuan Wu:
Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack. - Jim Zhao, Sidak Pal Singh, Aurélien Lucchi:
Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks. - Zipeng Xiao, Siqi Kou, Zhongkai Hao, Bokai Lin, Zhijie Deng:
Amortized Fourier Neural Operators. - Romain Ilbert, Malik Tiomoko, Cosme Louart, Ambroise Odonnat, Vasilii Feofanov, Themis Palpanas, Ievgen Redko:
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting. - Josselin Somerville Roberts, Tony Lee, Chi Heem Wong, Michihiro Yasunaga, Yifan Mai, Percy Liang:
Image2Struct: Benchmarking Structure Extraction for Vision-Language Models. - Shiye Lei, Sen Zhang, Dacheng Tao:
Offline Behavior Distillation. - Yidong Wang, Qi Guo, Wenjin Yao, Hongbo Zhang, Xin Zhang, Zhen Wu, Meishan Zhang, Xinyu Dai, Min Zhang, Qingsong Wen, Wei Ye, Shikun Zhang, Yue Zhang:
AutoSurvey: Large Language Models Can Automatically Write Surveys. - Henry Hengyuan Zhao, Pan Zhou, Difei Gao, Zechen Bai, Mike Zheng Shou:
LOVA3: Learning to Visual Question Answering, Asking and Assessment. - Xu Yang, Chen Liu, Ying Wei:
Mixture of Adversarial LoRAs: Boosting Robust Generalization in Meta-Tuning. - Jiadong Pan, Hongcheng Gao, Zongyu Wu, Taihang Hu, Li Su, Qingming Huang, Liang Li:
Leveraging Catastrophic Forgetting to Develop Safe Diffusion Models against Malicious Finetuning. - Shihao Tu, Yupeng Zhang, Jing Zhang, Zhendong Fu, Yin Zhang, Yang Yang:
PowerPM: Foundation Model for Power Systems. - Junnan Dong, Qinggang Zhang, Chuang Zhou, Hao Chen, Daochen Zha, Xiao Huang:
Cost-efficient Knowledge-based Question Answering with Large Language Models. - Sebastian Loeschcke, Mads Toftrup, Michael J. Kastoryano, Serge J. Belongie, Vésteinn Snæbjarnarson:
LoQT: Low-Rank Adapters for Quantized Pretraining. - Jiajie Tao, Hao Ni, Chong Liu:
High Rank Path Development: an approach to learning the filtration of stochastic processes. - Dongxiao He, Lianze Shan, Jitao Zhao, Hengrui Zhang, Zhen Wang, Weixiong Zhang:
Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering. - Weijian Luo, Zemin Huang, Zhengyang Geng, J. Zico Kolter, Guo-Jun Qi:
One-Step Diffusion Distillation through Score Implicit Matching. - Jialin Yu, Andreas Koukorinis, Nicolò Colombo, Yuchen Zhu, Ricardo Silva:
Structured Learning of Compositional Sequential Interventions. - Zaiwei Chen, Eric Mazumdar:
Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities. - Changcai Li, Zonghua Gu, Gang Chen, Libo Huang, Wei Zhang, Huihui Zhou:
Real-time Stereo-based 3D Object Detection for Streaming Perception. - Songlin Yang, Bailin Wang, Yu Zhang, Yikang Shen, Yoon Kim:
Parallelizing Linear Transformers with the Delta Rule over Sequence Length. - Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin:
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index. - Honghua Zhang, Po-Nien Kung, Masahiro Yoshida, Guy Van den Broeck, Nanyun Peng:
Adaptable Logical Control for Large Language Models. - Sheng-Chieh Lin, Luyu Gao, Barlas Oguz, Wenhan Xiong, Jimmy Lin, Scott Yih, Xilun Chen:
FLAME : Factuality-Aware Alignment for Large Language Models. - Feijie Wu, Xingchen Wang, Yaqing Wang, Tianci Liu, Lu Su, Jing Gao:
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction. - Nikita Karagodin, Yury Polyanskiy, Philippe Rigollet:
Clustering in Causal Attention Masking. - Simon Mataigne, Johan Mathe, Sophia Sanborn, Christopher Hillar, Nina Miolane:
The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks. - Haonan Lin, Yan Chen, Jiahao Wang, Wenbin An, Mengmeng Wang, Feng Tian, Yong Liu, Guang Dai, Jingdong Wang, Qianying Wang:
Schedule Your Edit: A Simple yet Effective Diffusion Noise Schedule for Image Editing. - Yadong Sun, Xiaofeng Cao, Yu Wang, Wei Ye, Jingcai Guo, Qing Guo:
Geometry Awakening: Cross-Geometry Learning Exhibits Superiority over Individual Structures. - Chengting Yu, Lei Liu, Gaoang Wang, Erping Li, Aili Wang:
Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation. - Artem Agafonov, Petr Ostroukhov, Roman Mozhaev, Konstantin Yakovlev, Eduard Gorbunov, Martin Takác, Alexander V. Gasnikov, Dmitry Kamzolov:
Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations. - Samuele Bortolotti, Emanuele Marconato, Tommaso Carraro, Paolo Morettin, Emile van Krieken, Antonio Vergari, Stefano Teso, Andrea Passerini:
A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts. - Yuval Ran-Milo, Eden Lumbroso, Edo Cohen-Karlik, Raja Giryes, Amir Globerson, Nadav Cohen:
Provable Benefits of Complex Parameterizations for Structured State Space Models. - Feiqing Huang, Shenghan Zhang, Sara Morini Sweet, Tianxi Cai:
A teacher-teacher framework for clinical language representation learning. - Michael Wornow, Avanika Narayan, Ben Viggiano, Ishan S. Khare, Tathagat Verma, Tibor Thompson, Miguel Angel Fuentes Hernandez, Sudharsan Sundar, Chloe Trujillo, Krrish Chawla, Rongfei Lu, Justin Shen, Divya Nagaraj, Joshua Martinez, Vardhan Agrawal, Althea Hudson, Nigam Shah, Christopher Ré:
WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks. - Lunjia Hu, Arun Jambulapati, Kevin Tian, Chutong Yang:
Testing Calibration in Nearly-Linear Time. - Chaoda Zheng, Feng Wang, Naiyan Wang, Shuguang Cui, Zhen Li:
Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection. - Divyam Madaan, Taro Makino, Sumit Chopra, Kyunghyun Cho:
Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning. - Théo Moutakanni, Maxime Oquab, Marc Szafraniec, Maria Vakalopoulou, Piotr Bojanowski:
You Don't Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learning. - Ruisi Cai, Yeonju Ro, Geon-Woo Kim, Peihao Wang, Babak Ehteshami Bejnordi, Aditya Akella, Zhangyang Wang:
Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design. - Hirofumi Tsuruta, Hiroyuki Yamazaki, Ryota Maeda, Ryotaro Tamura, Akihiro Imura:
A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models. - Xin-Chun Li, Jin-Lin Tang, Bo Zhang, Lan Li, De-Chuan Zhan:
Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks. - Fang Wu, Shuting Jin, Siyuan Li, Stan Z. Li:
Instructor-inspired Machine Learning for Robust Molecular Property Prediction. - Christopher Scarvelis, Justin M. Solomon:
Nuclear Norm Regularization for Deep Learning. - Ziming Wang, Rebecka Jörnsten:
SE(3)-bi-equivariant Transformers for Point Cloud Assembly. - Steve Hanneke, Mingyue Xu:
Universal Rates of Empirical Risk Minimization. - Yixiong Zou, Ran Ma, Yuhua Li, Ruixuan Li:
Attention Temperature Matters in ViT-Based Cross-Domain Few-Shot Learning. - Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim M. Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai:
LocCa: Visual Pretraining with Location-aware Captioners. - Shuwen Chai, Miklós Z. Rácz:
Efficient Graph Matching for Correlated Stochastic Block Models. - Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang:
RedPajama: an Open Dataset for Training Large Language Models. - Wenjun Zhang, Liangxiao Jiang, Chaoqun Li:
KFNN: K-Free Nearest Neighbor For Crowdsourcing. - Akshay Mehra, Yunbei Zhang, Jihun Hamm:
Understanding the Transferability of Representations via Task-Relatedness. - Weihao Lin, Shengji Tang, Chong Yu, Peng Ye, Tao Chen:
S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning. - Yilun Zhu, Jianxin Zhang, Aditya Gangrade, Clayton Scott:
Label Noise: Ignorance Is Bliss. - Richard Yuanzhe Pang, Weizhe Yuan, He He, Kyunghyun Cho, Sainbayar Sukhbaatar, Jason Weston:
Iterative Reasoning Preference Optimization. - Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis, Haifeng Xu:
Strategic Linear Contextual Bandits. - Jinqiu Li, Enmin Zhao, Tong Wei, Junliang Xing, Shiming Xiang:
Dual Critic Reinforcement Learning under Partial Observability. - Miguel Lázaro-Gredilla, Li Yang Ku, Kevin P. Murphy, Dileep George:
What type of inference is planning? - Zhihao Xu, Ruixuan Huang, Changyu Chen, Xiting Wang:
Uncovering Safety Risks of Large Language Models through Concept Activation Vector. - Fei Zhou, Peng Wang, Lei Zhang, Zhenghua Chen, Wei Wei, Chen Ding, Guosheng Lin, Yanning Zhang:
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning. - Yunzhe Hu, Difan Zou, Dong Xu:
An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models. - Yaming Guo, Chen Zhu, Hengshu Zhu, Tieru Wu:
OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation. - Yu Zhang, Songlin Yang, Rui-Jie Zhu, Yue Zhang, Leyang Cui, Yiqiao Wang, Bolun Wang, Freda Shi, Bailin Wang, Wei Bi, Peng Zhou, Guohong Fu:
Gated Slot Attention for Efficient Linear-Time Sequence Modeling. - Xiao Guo, Vishal Asnani, Sijia Liu, Xiaoming Liu:
Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network. - Kent W. Gauen, Stanley H. Chan:
Soft Superpixel Neighborhood Attention. - Di Zhang, Bowen Lv, Hai Zhang, Feifan Yang, Junqiao Zhao, Hang Yu, Chang Huang, Hongtu Zhou, Chen Ye, Changjun Jiang:
Focus On What Matters: Separated Models For Visual-Based RL Generalization. - Alireza Javanmardi, David Stutz, Eyke Hüllermeier:
Conformalized Credal Set Predictors. - Soufiane Hayou, Nikhil Ghosh, Bin Yu:
The Impact of Initialization on LoRA Finetuning Dynamics. - Zeyu Zhang, Lu Li, Shuyan Wan, Sijie Wang, Zhiyi Wang, Zhiyuan Lu, Dong Hao, Wanli Li:
DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks. - Vaskar Nath, Dylan Slack, Jeff Da, Yuntao Ma, Hugh Zhang, Spencer Whitehead, Sean Hendryx:
Learning Goal-Conditioned Representations for Language Reward Models. - Xuan-Bach Le, Dominik Wagner, Leon Witzman, Alexander Rabinovich, Luke Ong:
Reinforcement Learning with LTL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards. - Yancheng Wang, Rajeev Goel, Utkarsh Nath, Alvin C. Silva, Teresa Wu, Yingzhen Yang:
Learning Low-Rank Feature for Thorax Disease Classification. - Shicheng Liu, Minghui Zhu:
In-Trajectory Inverse Reinforcement Learning: Learn Incrementally Before an Ongoing Trajectory Terminates. - Nasibullah Nasibullah, Erik Schultheis, Mike Lasby, Yani Ioannou, Rohit Babbar:
Navigating Extremes: Dynamic Sparsity in Large Output Spaces. - Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao:
Truthfulness of Calibration Measures. - Zaizuo Tang, Yu-Bin Yang:
IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution. - Lincen Yang, Matthijs van Leeuwen:
Conditional Density Estimation with Histogram Trees. - Yuxi Ren, Xin Xia, Yanzuo Lu, Jiacheng Zhang, Jie Wu, Pan Xie, Xing Wang, Xuefeng Xiao:
Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis. - Zhangyi Hu, Bin Yang, Mang Ye:
Empowering Visible-Infrared Person Re-Identification with Large Foundation Models. - Jian Song, Hongruixuan Chen, Weihao Xuan, Junshi Xia, Naoto Yokoya:
SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagery. - Taiyu Ban, Lyuzhou Chen, Xiangyu Wang, Xin Wang, Derui Lyu, Huanhuan Chen:
Differentiable Structure Learning with Partial Orders. - Zhiyuan Ma, Liangliang Zhao, Biqing Qi, Bowen Zhou:
Neural Residual Diffusion Models for Deep Scalable Vision Generation. - Yujia Jin, Ishani Karmarkar, Aaron Sidford, Jiayi Wang:
Truncated Variance Reduced Value Iteration. - Rashida Hakim, Ana-Andreea Stoica, Christos H. Papadimitriou, Mihalis Yannakakis:
The Fairness-Quality Tradeoff in Clustering. - Intekhab Hossain, Jonas Fischer, Rebekka Burkholz, John Quackenbush:
Pruning neural network models for gene regulatory dynamics using data and domain knowledge. - Tavor Z. Baharav, Ryan Kang, Colin Sullivan, Mo Tiwari, Eric Luxenberg, David Tse, Mert Pilanci:
Adaptive Sampling for Efficient Softmax Approximation. - Bowen Jin, Ziqi Pang, Bingjun Guo, Yu-Xiong Wang, Jiaxuan You, Jiawei Han:
InstructG2I: Synthesizing Images from Multimodal Attributed Graphs. - Wei Liu, Zhiying Deng, Zhongyu Niu, Jun Wang, Haozhao Wang, YuanKai Zhang, Ruixuan Li:
Is the MMI Criterion Necessary for Interpretability? Degenerating Non-causal Features to Plain Noise for Self-Rationalization. - Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell:
Oracle-Efficient Reinforcement Learning for Max Value Ensembles. - Fei Xie, Weijia Zhang, Zhongdao Wang, Chao Ma:
QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model. - Mingyu Chen, Aldo Pacchiano, Xuezhou Zhang:
State-free Reinforcement Learning. - Javier Gonzalez, Aditya Nori:
Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models. - Junlin Wu, Huan Zhang, Yevgeniy Vorobeychik:
Verified Safe Reinforcement Learning for Neural Network Dynamic Models. - Huayu Chen, Guande He, Lifan Yuan, Ganqu Cui, Hang Su, Jun Zhu:
Noise Contrastive Alignment of Language Models with Explicit Rewards. - Shai Feldman, Yaniv Romano:
Robust Conformal Prediction Using Privileged Information. - Jinghui Lu, Yanjie Wang, Ziwei Yang, Xuejing Liu, Brian Mac Namee, Can Huang:
PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition. - Hengkang Wang, Xu Zhang, Taihui Li, Yuxiang Wan, Tiancong Chen, Ju Sun:
DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models. - Gayane Taturyan, Evgenii Chzhen, Mohamed Hebiri:
Regression under demographic parity constraints via unlabeled post-processing. - Hao Tang, Keya Hu, Jin Zhou, Sicheng Zhong, Wei-Long Zheng, Xujie Si, Kevin Ellis:
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff. - Jinmin He, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng:
Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance. - Anisha Pal, Julia Kruk, Mansi Phute, Manognya Bhattaram, Diyi Yang, Duen Horng Chau, Judy Hoffman:
Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors. - Luckeciano Carvalho Melo, Panagiotis Tigas, Alessandro Abate, Yarin Gal:
Deep Bayesian Active Learning for Preference Modeling in Large Language Models. - Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael I. Jordan, Ramesh Raskar:
Data Acquisition via Experimental Design for Data Markets. - Jaivardhan Kapoor, Auguste Schulz, Julius Vetter, Felix Pei, Richard Gao, Jakob H. Macke:
Latent Diffusion for Neural Spiking Data. - JunHoo Lee, Hyunho Lee, Kyomin Hwang, Nojun Kwak:
Deep Support Vectors. - Wang Lin, Yueying Feng, WenKang Han, Tao Jin, Zhou Zhao, Fei Wu, Chang Yao, Jingyuan Chen:
E3: Exploring Embodied Emotion Through A Large-Scale Egocentric Video Dataset. - Chris Yuhao Liu, Yaxuan Wang, Jeffrey Flanigan, Yang Liu:
Large Language Model Unlearning via Embedding-Corrupted Prompts. - Andi Han, Jiaxiang Li, Wei Huang, Mingyi Hong, Akiko Takeda, Pratik Kumar Jawanpuria, Bamdev Mishra:
SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining. - Nicolas Beltran-Velez, Alessandro Antonio Grande, Achille Nazaret, Alp Kucukelbir, David M. Blei:
Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees. - Jianqiao Zhang, Caifeng Shan, Jungong Han:
FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation. - Huy Nguyen, Nhat Ho, Alessandro Rinaldo:
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts. - Zihui Wu, Yu Sun, Yifan Chen, Bingliang Zhang, Yisong Yue, Katherine L. Bouman:
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors. - Bingqi Ma, Zhuofan Zong, Guanglu Song, Hongsheng Li, Yu Liu:
Exploring the Role of Large Language Models in Prompt Encoding for Diffusion Models. - Hongyu Sun, Qiuhong Ke, Yongcai Wang, Wang Chen, Kang Yang, Deying Li, Jianfei Cai:
Point-PRC: A Prompt Learning Based Regulation Framework for Generalizable Point Cloud Analysis. - Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu:
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. - Gang Ding, Zeyuan Liu, Zhirui Fang, Kefan Su, Liwen Zhu, Zongqing Lu:
Multi-Agent Coordination via Multi-Level Communication. - Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller, Oliver Eberle:
MambaLRP: Explaining Selective State Space Sequence Models. - Yunzhi Yao, Ningyu Zhang, Zekun Xi, Mengru Wang, Ziwen Xu, Shumin Deng, Huajun Chen:
Knowledge Circuits in Pretrained Transformers. - Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, Sanjeev Arora:
Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates. - Yuan Zhang, Fei Xiao, Tao Huang, Chun-Kai Fan, Hongyuan Dong, Jiawen Li, Jiacong Wang, Kuan Cheng, Shanghang Zhang, Haoyuan Guo:
Unveiling the Tapestry of Consistency in Large Vision-Language Models. - Sunjae Yoon, Gwanhyeong Koo, Younghwan Lee, Chang Dong Yoo:
TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation. - Erfan Hajihashemi, Yanning Shen:
Multi-model Ensemble Conformal Prediction in Dynamic Environments. - Mingze Wang, Jinbo Wang, Haotian He, Zilin Wang, Guanhua Huang, Feiyu Xiong, Zhiyu Li, Weinan E, Lei Wu:
Improving Generalization and Convergence by Enhancing Implicit Regularization. - Samuel Lippl, Jack W. Lindsey:
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse. - Miruna Oprescu, Nathan Kallus:
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data. - Shraman Pramanick, Rama Chellappa, Subhashini Venugopalan:
SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers. - Ethan Shen, Alan Fan, Sarah M. Pratt, Jae Sung Park, Matthew Wallingford, Sham M. Kakade, Ari Holtzman, Ranjay Krishna, Ali Farhadi, Aditya Kusupati:
Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass. - Franck Iutzeler, Edouard Pauwels, Samuel Vaiter:
Derivatives of Stochastic Gradient Descent in parametric optimization. - Hongbo Wang, Jie Cao, Jin Liu, Xiaoqiang Zhou, Huaibo Huang, Ran He:
Hallo3D: Multi-Modal Hallucination Detection and Mitigation for Consistent 3D Content Generation. - Polina Turishcheva, Paul G. Fahey, Michaela Vystrcilová, Laura Hansel, Rachel Froebe, Kayla Ponder, Yongrong Qiu, Konstantin Willeke, Mohammad Bashiri, Ruslan Baikulov, Yu Zhu, Lei Ma, Shan Yu, Tiejun Huang, Bryan Li, Wolf De Wulf, Nina Kudryashova, Matthias H. Hennig, Nathalie Rochefort, Arno Onken, Eric Y. Wang, Zhiwei Ding, Andreas S. Tolias, Fabian H. Sinz, Alexander S. Ecker:
Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos. - Abdulkadir Çelikkanat, Andrés R. Masegosa, Thomas Nielsen:
Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning. - Lior Shani, Aviv Rosenberg, Asaf Cassel, Oran Lang, Daniele Calandriello, Avital Zipori, Hila Noga, Orgad Keller, Bilal Piot, Idan Szpektor, Avinatan Hassidim, Yossi Matias, Rémi Munos:
Multi-turn Reinforcement Learning with Preference Human Feedback. - Takuo Matsubara:
Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning. - Minh Le, An Nguyen The, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Ngo Van, Nhat Ho:
Mixture of Experts Meets Prompt-Based Continual Learning. - Juelin Zhu, Shen Yan, Long Wang, Shengyue Zhang, Yu Liu, Maojun Zhang:
LoD-Loc: Aerial Visual Localization using LoD 3D Map with Neural Wireframe Alignment. - Isabelle Hurley, Rohan Paleja, Ashley Suh, Jaime Daniel Peña, Ho Chit Siu:
STL: Still Tricky Logic (for System Validation, Even When Showing Your Work). - Joachim Baumann, Celestine Mendler-Dünner:
Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists. - David Winkel, Niklas Strauß, Maximilian Bernhard, Zongyue Li, Thomas Seidl, Matthias Schubert:
Autoregressive Policy Optimization for Constrained Allocation Tasks. - Jiawen Zhang, Shun Zheng, Xumeng Wen, Xiaofang Zhou, Jiang Bian, Jia Li:
ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer. - Rui Li, Tingting Ren, Jie Wen, Jinxing Li:
Optimal Transport-based Labor-free Text Prompt Modeling for Sketch Re-identification. - Elliot Meyerson, Olivier Francon, Darren Sargent, Babak Hodjat, Risto Miikkulainen:
Unlocking the Potential of Global Human Expertise. - Minghao Guo, Bohan Wang, Pingchuan Ma, Tianyuan Zhang, Crystal Elaine Owens, Chuang Gan, Josh Tenenbaum, Kaiming He, Wojciech Matusik:
Physically Compatible 3D Object Modeling from a Single Image. - Ding Qi, Jian Li, Jinlong Peng, Bo Zhao, Shuguang Dou, Jialin Li, Jiangning Zhang, Yabiao Wang, Chengjie Wang, Cairong Zhao:
Fetch and Forge: Efficient Dataset Condensation for Object Detection. - Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Géraud Krawezik, François Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho:
Multiple Physics Pretraining for Spatiotemporal Surrogate Models. - Rui Qian, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Shuangrui Ding, Dahua Lin, Jiaqi Wang:
Streaming Long Video Understanding with Large Language Models. - Qi Song, Ziyuan Luo, Ka Chun Cheung, Simon See, Renjie Wan:
Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images. - Liyi Chen, Ying Sun, Shengzhe Zhang, Yuyang Ye, Wei Wu, Hui Xiong:
Tackling Uncertain Correspondences for Multi-Modal Entity Alignment. - Heng Li, Minghan Li, Zhi-Qi Cheng, Yifei Dong, Yuxuan Zhou, Jun-Yan He, Qi Dai, Teruko Mitamura, Alexander G. Hauptmann:
Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions. - Jiawei Du, Xin Zhang, Juncheng Hu, Wenxin Huang, Joey Tianyi Zhou:
Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment. - Zhongshen Zeng, Yinhong Liu, Yingjia Wan, Jingyao Li, Pengguang Chen, Jianbo Dai, Yuxuan Yao, Rongwu Xu, Zehan Qi, Wanru Zhao, Linling Shen, Jianqiao Lu, Haochen Tan, Yukang Chen, Hao Zhang, Zhan Shi, Bailin Wang, Zhijiang Guo, Jiaya Jia:
MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs. - David McSharry, Christos Kaplanis, Fernando Rosas, Pedro A. M. Mediano:
Learning diverse causally emergent representations from time series data. - Xingwu Chen, Lei Zhao, Difan Zou:
How Transformers Utilize Multi-Head Attention in In-Context Learning? A Case Study on Sparse Linear Regression. - Yipu Chen, Haotian Xue, Yongxin Chen:
Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies. - Chaojun Xiao, Pengle Zhang, Xu Han, Guangxuan Xiao, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Maosong Sun:
InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory. - Siwei Wang, Yifei Shen, Shi Feng, Haoran Sun, Shang-Hua Teng, Wei Chen:
ALPINE: Unveiling The Planning Capability of Autoregressive Learning in Language Models. - Minki Kang, Sung Ju Hwang, Gibbeum Lee, Jaewoong Cho:
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models. - Jianning Deng, Kartic Subr, Hakan Bilen:
Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis. - Jonathan So, Richard E. Turner:
Fearless Stochasticity in Expectation Propagation. - Yuzheng Hu, Pingbang Hu, Han Zhao, Jiaqi W. Ma:
Most Influential Subset Selection: Challenges, Promises, and Beyond. - Nazar Buzun, Maksim Bobrin, Dmitry V. Dylov:
Expectile Regularization for Fast and Accurate Training of Neural Optimal Transport. - Yichong Huang, Xiaocheng Feng, Baohang Li, Yang Xiang, Hui Wang, Ting Liu, Bing Qin:
Ensemble Learning for Heterogeneous Large Language Models with Deep Parallel Collaboration. - Jiabao Wang, Zhaojiang Liu, Qiang Meng, Liujiang Yan, Ke Wang, Jie Yang, Wei Liu, Qibin Hou, Ming-Ming Cheng:
OPUS: Occupancy Prediction Using a Sparse Set. - Ali Behrouz, Michele Santacatterina, Ramin Zabih:
Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models. - Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee:
AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents. - Huayu Chen, Kaiwen Zheng, Hang Su, Jun Zhu:
Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control. - Botos Csaba, Wenxuan Zhang, Matthias Müller, Ser Nam Lim, Philip Torr, Adel Bibi:
Label Delay in Online Continual Learning. - Zeyue Zhang, Xiaoling Lu, Feng Zhou:
Conjugate Bayesian Two-step Change Point Detection for Hawkes Process. - Kevin Tan, Wei Fan, Yuting Wei:
Hybrid Reinforcement Learning Breaks Sample Size Barriers In Linear MDPs. - Kurt Butler, Daniel Waxman, Petar M. Djuric:
Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems. - Emir Konuk, Christos Matsoukas, Moein Sorkhei, Phitchapha Lertsiravarameth, Kevin Smith:
Learning from Offline Foundation Features with Tensor Augmentations. - Akshay Krishnamurthy, Keegan Harris, Dylan J. Foster, Cyril Zhang, Aleksandrs Slivkins:
Can large language models explore in-context? - Haoyu Wang, Zhuo Huang, Zhiwei Lin, Tongliang Liu:
NoiseGPT: Label Noise Detection and Rectification through Probability Curvature. - Eungyeup Kim, Mingjie Sun, Christina Baek, Aditi Raghunathan, J. Zico Kolter:
Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line. - Paolo Pellizzoni, Till Hendrik Schulz, Dexiong Chen, Karsten M. Borgwardt:
On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks. - Felix Koehler, Simon Niedermayr, Rüdiger Westermann, Nils Thuerey:
APEBench: A Benchmark for Autoregressive Neural Emulators of PDEs. - Bing Cao, Xingxin Xu, Pengfei Zhu, Qilong Wang, Qinghua Hu:
Conditional Controllable Image Fusion. - Yusong Wang, Chaoran Cheng, Shaoning Li, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, Nanning Zheng:
Neural P3M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs. - Nuwan Sriyantha Bandara, Thivya Kandappu, Argha Sen, Ila Gokarn, Archan Misra:
EyeGraph: Modularity-aware Spatio Temporal Graph Clustering for Continuous Event-based Eye Tracking. - Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun, Huawei Shen, Xueqi Cheng:
Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation. - Silong Yong, Yaqi Xie, Simon Stepputtis, Katia P. Sycara:
GL-NeRF: Gauss-Laguerre Quadrature Enables Training-Free NeRF Acceleration. - Yunyue Wei, Vincent Zhuang, Saraswati Soedarmadji, Yanan Sui:
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes. - Junfeng Guo, Yiming Li, Ruibo Chen, Yihan Wu, Chenxi Liu, Heng Huang:
ZeroMark: Towards Dataset Ownership Verification without Disclosing Watermark. - Kai Xiong, Xiao Ding, Ting Liu, Bing Qin, Dongliang Xu, Qing Yang, Hongtao Liu, Yixin Cao:
Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance. - Sheng Wu, Hang Sheng, Hui Feng, Bo Hu:
EGSST: Event-based Graph Spatiotemporal Sensitive Transformer for Object Detection. - Yexiong Lin, Yu Yao, Tongliang Liu:
Learning the Latent Causal Structure for Modeling Label Noise. - Yaoyuan Liang, Zhuojun Cai, Jian Xu, Guanbo Huang, Yiran Wang, Xiao Liang, Jiahao Liu, Ziran Li, Jingang Wang, Shao-Lun Huang:
Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation. - Dylan J. Foster, Adam Block, Dipendra Misra:
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning. - Yuval Dagan, Michael I. Jordan, Xuelin Yang, Lydia Zakynthinou, Nikita Zhivotovskiy:
Dimension-free Private Mean Estimation for Anisotropic Distributions. - Zhengyang Yu, Zhaoyuan Yang, Jing Zhang:
DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion Models. - Hanna Yukhymenko, Robin Staab, Mark Vero, Martin T. Vechev:
A Synthetic Dataset for Personal Attribute Inference. - Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok:
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning. - Wenrui Hao, Xinliang Liu, Yahong Yang:
Newton Informed Neural Operator for Solving Nonlinear Partial Differential Equations. - Xiangxin Zhou, Dongyu Xue, Ruizhe Chen, Zaixiang Zheng, Liang Wang, Quanquan Gu:
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization. - Azim Ospanov, Jingwei Zhang, Mohammad Jalali, Xuenan Cao, Andrej Bogdanov, Farzan Farnia:
Towards a Scalable Reference-Free Evaluation of Generative Models. - Qibo Qiu, Shun Zhang, Haiming Gao, Honghui Yang, Haochao Ying, Wenxiao Wang, Xiaofei He:
EMVP: Embracing Visual Foundation Model for Visual Place Recognition with Centroid-Free Probing. - Wenke Huang, Mang Ye, Zekun Shi, Guancheng Wan, He Li, Bo Du:
Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning. - Weiqin Yang, Jiawei Chen, Xin Xin, Sheng Zhou, Binbin Hu, Yan Feng, Chun Chen, Can Wang:
PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation. - Shenbao Yu, Yinghui Pan, Yifeng Zeng, Prashant Doshi, Guoquan Liu, Kim-Leng Poh, Mingwei Lin:
An Autoencoder-Like Nonnegative Matrix Co-Factorization for Improved Student Cognitive Modeling. - Fanxu Meng, Zhaohui Wang, Muhan Zhang:
PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models. - Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro:
Provably Efficient Interactive-Grounded Learning with Personalized Reward. - Seunghan Lee, Kibok Lee, Taeyoung Park:
ANT: Adaptive Noise Schedule for Time Series Diffusion Models. - Jingjing Wang, Minhuan Huang, Yuanping Nie, Xiang Li, Qianjin Du, Wei Kong, Huan Deng, Xiaohui Kuang:
Suitable is the Best: Task-Oriented Knowledge Fusion in Vulnerability Detection. - Yue Yu, Wei Ping, Zihan Liu, Boxin Wang, Jiaxuan You, Chao Zhang, Mohammad Shoeybi, Bryan Catanzaro:
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs. - Felix Petersen, Hilde Kuehne, Christian Borgelt, Julian Welzel, Stefano Ermon:
Convolutional Differentiable Logic Gate Networks. - Yuxuan Gu, Xiaocheng Feng, Lei Huang, Yingsheng Wu, Zekun Zhou, Weihong Zhong, Kun Zhu, Bing Qin:
Discrete Modeling via Boundary Conditional Diffusion Processes. - Yanxin Yang, Chentao Jia, Dengke Yan, Ming Hu, Tianlin Li, Xiaofei Xie, Xian Wei, Mingsong Chen:
SampDetox: Black-box Backdoor Defense via Perturbation-based Sample Detoxification. - Hsiang Hsu, Ivan Brugere, Shubham Sharma, Freddy Lécué, Richard Chen:
RashomonGB: Analyzing the Rashomon Effect and Mitigating Predictive Multiplicity in Gradient Boosting. - Tong Yang, Shicong Cen, Yuting Wei, Yuxin Chen, Yuejie Chi:
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning. - Nitesh Bharadwaj Gundavarapu, Luke Friedman, Raghav Goyal, Chaitra Hegde, Eirikur Agustsson, Sagar Waghmare, Mikhail Sirotenko, Ming-Hsuan Yang, Tobias Weyand, Boqing Gong, Leonid Sigal:
Extending Video Masked Autoencoders to 128 frames. - Ruiming Guo, Mouxing Yang, Yijie Lin, Xi Peng, Peng Hu:
Robust Contrastive Multi-view Clustering against Dual Noisy Correspondence. - Samy Tafasca, Anshul Gupta, Victor Bros, Jean-Marc Odobez:
Toward Semantic Gaze Target Detection. - Baiting Chen, Zhimei Ren, Lu Cheng:
Conformalized Time Series with Semantic Features. - Weihan Wang, Qingsong Lv, Wenmeng Yu, Wenyi Hong, Ji Qi, Yan Wang, Junhui Ji, Zhuoyi Yang, Lei Zhao, Xixuan Song, Jiazheng Xu, Keqin Chen, Bin Xu, Juanzi Li, Yuxiao Dong, Ming Ding, Jie Tang:
CogVLM: Visual Expert for Pretrained Language Models. - Xinyue Luo, Jin Cheng, Yu Chen:
MeLLoC: Lossless Compression with High-order Mechanism Learning. - Jiashun Liu, Jianye Hao, Xiaotian Hao, Yi Ma, Yan Zheng, Yujing Hu, Tangjie Lv:
Unlock the Intermittent Control Ability of Model Free Reinforcement Learning. - Chengyuan Deng, Jie Gao, Kevin Lu, Feng Luo, Hongbin Sun, Cheng Xin:
Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms. - Per Kristian Lehre, Shishen Lin:
No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation. - Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar:
The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations. - Haiyi Mao, Romain Lopez, Kai Liu, Jan-Christian Huetter, David Richmond, Panayiotis V. Benos, Lin Qiu:
Learning Identifiable Factorized Causal Representations of Cellular Responses. - Ming Dai, Lingfeng Yang, Yihao Xu, Zhenhua Feng, Wankou Yang:
SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion. - Ilan Naiman, Nimrod Berman, Itai Pemper, Idan Arbiv, Gal Fadlon, Omri Azencot:
Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series. - Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, Zhiqi Shen:
Collaboration! Towards Robust Neural Methods for Routing Problems. - Jan-Niklas Dihlmann, Arjun Majumdar, Andreas Engelhardt, Raphael Braun, Hendrik P. A. Lensch:
Subsurface Scattering for Gaussian Splatting. - Wonil Song, Hyesong Choi, Kwanghoon Sohn, Dongbo Min:
A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations. - Yu Zheng, Guangming Wang, Jiuming Liu, Marc Pollefeys, Hesheng Wang:
Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation. - Shuang Wu, Youtian Lin, Yifei Zeng, Feihu Zhang, Jingxi Xu, Philip Torr, Xun Cao, Yao Yao:
Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer. - Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli:
Optimal Multi-Fidelity Best-Arm Identification. - Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain:
Adaptive Experimentation When You Can't Experiment. - King-Siong Si, Lu Sun, Weizhan Zhang, Tieliang Gong, Jiahao Wang, Jiang Liu, Hao Sun:
Accelerating Non-Maximum Suppression: A Graph Theory Perspective. - Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus:
Targeted Sequential Indirect Experiment Design. - Xiufeng Song, Xiao Guo, Jiache Zhang, Qirui Li, Lei Bai, Xiaoming Liu, Guangtao Zhai, Xiaohong Liu:
On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection. - Yuwei Fu, Haichao Zhang, Di Wu, Wei Xu, Benoit Boulet:
Robot Policy Learning with Temporal Optimal Transport Reward. - Rui Zhao, Hangjie Yuan, Yujie Wei, Shiwei Zhang, Yuchao Gu, Lingmin Ran, Xiang Wang, Jay Zhangjie Wu, David Junhao Zhang, Yingya Zhang, Mike Zheng Shou:
EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models. - Xinhai Zhang, Xingye Qiao:
A Non-parametric Direct Learning Approach to Heterogeneous Treatment Effect Estimation under Unmeasured Confounding. - Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, Mingsheng Long:
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models. - Yi Zhu, Yanpeng Zhou, Chunwei Wang, Yang Cao, Jianhua Han, Lu Hou, Hang Xu:
UNIT: Unifying Image and Text Recognition in One Vision Encoder. - Tian Huang, Shengbo Wang, Ke Li:
Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandits. - Sho Yokoi, Han Bao, Hiroto Kurita, Hidetoshi Shimodaira:
Zipfian Whitening. - Tianyi Zhang, Linrong Cai, Jeffrey Li, Nicholas Roberts, Neel Guha, Frederic Sala:
Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks. - Zekun Shi, Zheyuan Hu, Min Lin, Kenji Kawaguchi:
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators. - Yu Zhao, Hao Fei, Xiangtai Li, Libo Qin, Jiayi Ji, Hongyuan Zhu, Meishan Zhang, Min Zhang, Jianguo Wei:
Synergistic Dual Spatial-aware Generation of Image-to-text and Text-to-image. - Josquin Harrison, James Benn, Maxime Sermesant:
Improving Neural Network Surface Processing with Principal Curvatures. - Can Demircan, Tankred Saanum, Leonardo Pettini, Marcel Binz, Blazej M. Baczkowski, Christian F. Doeller, Mona M. Garvert, Eric Schulz:
Evaluating alignment between humans and neural network representations in image-based learning tasks. - Zhaoliang Zhang, Tianchen Song, Yongjae Lee, Li Yang, Cheng Peng, Rama Chellappa, Deliang Fan:
LP-3DGS: Learning to Prune 3D Gaussian Splatting. - Tuomas Kynkäänniemi, Miika Aittala, Tero Karras, Samuli Laine, Timo Aila, Jaakko Lehtinen:
Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models. - Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang:
A Sober Look at the Robustness of CLIPs to Spurious Features. - Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Felix Krahmer, Holger Rauhut:
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning. - Zibin Dong, Jianye Hao, Yifu Yuan, Fei Ni, Yitian Wang, Pengyi Li, Yan Zheng:
DiffuserLite: Towards Real-time Diffusion Planning. - Hongtai Zeng, Chao Yang, Yanzhen Zhou, Cheng Yang, Qinglai Guo:
GLinSAT: The General Linear Satisfiability Neural Network Layer By Accelerated Gradient Descent. - Shima Adeli, Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh:
Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy. - Alexander Tyurin, Peter Richtárik:
On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization. - Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars. - Chenyu Huang, Peng Ye, Tao Chen, Tong He, Xiangyu Yue, Wanli Ouyang:
EMR-Merging: Tuning-Free High-Performance Model Merging. - Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic:
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms. - Xinyu Lyu, Beitao Chen, Lianli Gao, Hengtao Shen, Jingkuan Song:
Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization. - Qilong Ma, Haixu Wu, Lanxiang Xing, Shangchen Miao, Mingsheng Long:
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction. - Junfeng Fang, Zac Bi, Ruipeng Wang, Houcheng Jiang, Yuan Gao, Kun Wang, An Zhang, Jie Shi, Xiang Wang, Tat-Seng Chua:
Towards Neuron Attributions in Multi-Modal Large Language Models. - Xi Gao, Jinxin Xiong, Akang Wang, Qihong Duan, Jiang Xue, Qingjiang Shi:
IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs. - Guohao Chen, Shuaicheng Niu, Deyu Chen, Shuhai Zhang, Changsheng Li, Yuanqing Li, Mingkui Tan:
Cross-Device Collaborative Test-Time Adaptation. - Kun Yuan, Vinkle Srivastav, Nassir Navab, Nicolas Padoy:
Procedure-Aware Surgical Video-language Pretraining with Hierarchical Knowledge Augmentation. - Hongling Zheng, Li Shen, Yong Luo, Tongliang Liu, Jialie Shen, Dacheng Tao:
Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization. - Jie Shao, Ke Zhu, Hanxiao Zhang, Jianxin Wu:
DiffuLT: Diffusion for Long-tail Recognition Without External Knowledge. - Yutao Mou, Shikun Zhang, Wei Ye:
SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Types. - Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Joshua T. Vogelstein, Pratik Chaudhari:
Prospective Learning: Learning for a Dynamic Future. - Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard, Nadia Oudjane:
MetaCURL: Non-stationary Concave Utility Reinforcement Learning. - Yansong Ning, Hao Liu:
UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction. - Antonio Montanaro, Luca Savant Aira, Emanuele Aiello, Diego Valsesia, Enrico Magli:
MotionCraft: Physics-Based Zero-Shot Video Generation. - Yanyi Zhang, Binglin Qiu, Qi Jia, Yu Liu, Ran He:
Not Just Object, But State: Compositional Incremental Learning without Forgetting. - Libo Qin, Qiguang Chen, Hao Fei, Zhi Chen, Min Li, Wanxiang Che:
What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration. - Haomeng Zhang, Chiao-An Yang, Raymond A. Yeh:
Multi-Object 3D Grounding with Dynamic Modules and Language-Informed Spatial Attention. - Jianbiao Mei, Yukai Ma, Xuemeng Yang, Licheng Wen, Xinyu Cai, Xin Li, Daocheng Fu, Bo Zhang, Pinlong Cai, Min Dou, Botian Shi, Liang He, Yong Liu, Yu Qiao:
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving. - Francesco Damiani, Akiyuki Anzai, Jan Drugowitsch, Gregory C. DeAngelis, Rubén Moreno-Bote:
Stochastic Optimal Control and Estimation with Multiplicative and Internal Noise. - Tarun Suresh, Debangshu Banerjee, Gagandeep Singh:
Relational Verification Leaps Forward with RABBit. - Hanyang Chen, Yang Jiang, Shengnan Guo, Xiaowei Mao, Youfang Lin, Huaiyu Wan:
DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data. - Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu:
Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference. - Trung-Hieu Hoang, MinhDuc Vo, Minh Do:
Persistent Test-time Adaptation in Recurring Testing Scenarios. - Burouj Armgaan, Manthan Dalmia, Sourav Medya, Sayan Ranu:
GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules. - Zhenyu Guan, Xiangyu Kong, Fangwei Zhong, Yizhou Wang:
Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy. - Alan Jeffares, Alicia Curth, Mihaela van der Schaar:
Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond. - Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang:
Towards Understanding Extrapolation: a Causal Lens. - Yanting Miao, William Loh, Suraj Kothawade, Pascal Poupart, Abdullah Rashwan, Yeqing Li:
Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning. - Arip Asadulaev, Rostislav Korst, Aleksandr Korotin, Vage Egiazarian, Andrey Filchenkov, Evgeny Burnaev:
Rethinking Optimal Transport in Offline Reinforcement Learning. - Sebastiaan De Peuter, Shibei Zhu, Yujia Guo, Andrew Howes, Samuel Kaski:
Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice. - Davide Legacci, Panayotis Mertikopoulos, Christos H. Papadimitriou, Georgios Piliouras, Bary S. R. Pradelski:
No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests. - Jiseok Chae, Chulhee Yun, Donghwan Kim:
Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements. - Chiraag Kaushik, Justin Romberg, Vidya Muthukumar:
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks. - Jiawei Xu, Zexin Fan, Jian Yang, Jin Xie:
Grid4D: 4D Decomposed Hash Encoding for High-Fidelity Dynamic Gaussian Splatting. - Ziqi Xie, Weidong Zhao, Xianhui Liu, Jian Zhao, Ning Jia:
Reconstructing the Image Stitching Pipeline: Integrating Fusion and Rectangling into a Unified Inpainting Model. - Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang, Bo Han:
Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales? - Katharina Limbeck, Rayna Andreeva, Rik Sarkar, Bastian Rieck:
Metric Space Magnitude for Evaluating the Diversity of Latent Representations. - Jen Ning Lim, Adam M. Johansen:
Particle Semi-Implicit Variational Inference. - Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin:
Rethinking the Capacity of Graph Neural Networks for Branching Strategy. - Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama, Federico Errica, Henrik Christiansen, Makoto Takamoto, Nicolas Weber, Mathias Niepert:
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing. - Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic:
LLM Dataset Inference: Did you train on my dataset? - Alexander Bukharin, Ilgee Hong, Haoming Jiang, Zichong Li, Qingru Zhang, Zixuan Zhang, Tuo Zhao:
Robust Reinforcement Learning from Corrupted Human Feedback. - Ziyi Yang, Chenyanzhen, Xinyu Gao, Yazhen Yuan, Yu Wu, Xiaowei Zhou, Xiaogang Jin:
RobIR: Robust Inverse Rendering for High-Illumination Scenes. - Vinamra Benara, Chandan Singh, John X. Morris, Richard J. Antonello, Ion Stoica, Alexander Huth, Jianfeng Gao:
Crafting Interpretable Embeddings for Language Neuroscience by Asking LLMs Questions. - Ziyad Benomar, Christian Coester:
Learning-Augmented Priority Queues. - Yu Meng, Mengzhou Xia, Danqi Chen:
SimPO: Simple Preference Optimization with a Reference-Free Reward. - Hanmin Li, Kirill Acharya, Peter Richtárik:
The Power of Extrapolation in Federated Learning. - Jiaxiang Li, Siliang Zeng, Hoi-To Wai, Chenliang Li, Alfredo García, Mingyi Hong:
Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment. - Sjoerd van Steenkiste, Daniel Zoran, Yi Yang, Yulia Rubanova, Rishabh Kabra, Carl Doersch, Dilara Gokay, Joseph Heyward, Etienne Pot, Klaus Greff, Drew A. Hudson, Thomas Keck, João Carreira, Alexey Dosovitskiy, Mehdi S. M. Sajjadi, Thomas Kipf:
Moving Off-the-Grid: Scene-Grounded Video Representations. - Abhinav Dutta, Sanjeev Krishnan, Nipun Kwatra, Ramachandran Ramjee:
Accuracy is Not All You Need. - Dominik A. Kloepfer, João F. Henriques, Dylan Campbell:
LoCo: Learning 3D Location-Consistent Image Features with a Memory-Efficient Ranking Loss. - Lirui Wang, Xinlei Chen, Jialiang Zhao, Kaiming He:
Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers. - Oyku Deniz Kose, Yanning Shen:
FairWire: Fair Graph Generation. - Jiapeng Ji, Kun Wei, Ziqi Zhang, Cheng Deng:
ACFun: Abstract-Concrete Fusion Facial Stylization. - Qiwen Cui, Maryam Fazel, Simon S. Du:
Learning Optimal Tax Design in Nonatomic Congestion Games. - Pranav Singh Chib, Pravendra Singh:
Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking. - Jiawei Wang, Renhe Jiang, Chuang Yang, Zengqing Wu, Makoto Onizuka, Ryosuke Shibasaki, Noboru Koshizuka, Chuan Xiao:
Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation. - Sunjun Kweon, Jiyoun Kim, Heeyoung Kwak, Dongchul Cha, Hangyul Yoon, Kwang Kim, Jeewon Yang, Seunghyun Won, Edward Choi:
EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries. - Chuning Zhu, Xinqi Wang, Tyler Han, Simon S. Du, Abhishek Gupta:
Distributional Successor Features Enable Zero-Shot Policy Optimization. - Junghyun Lee, Se-Young Yun, Kwang-Sung Jun:
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits. - Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause:
Transductive Active Learning: Theory and Applications. - Yuheng Zhang, Nan Jiang:
On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation. - Mingkun Zhang, Keping Bi, Wei Chen, Quanrun Chen, Jiafeng Guo, Xueqi Cheng:
CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense. - Jacob Adkins, Michael Bowling, Adam White:
A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning. - Sam Adam-Day, Michael Benedikt, Ismail Ilkan Ceylan, Ben Finkelshtein:
Almost Surely Asymptotically Constant Graph Neural Networks. - Yuewen Sun, Biwei Huang, Yu Yao, Donghuo Zeng, Xinshuai Dong, Songyao Jin, Boyang Sun, Roberto Legaspi, Kazushi Ikeda, Peter Spirtes, Kun Zhang:
Identifying Latent State-Transition Processes for Individualized Reinforcement Learning. - Kevin Slagle:
SpaceByte: Towards Deleting Tokenization from Large Language Modeling. - Jiaxing Huang, Jingyi Zhang, Kai Jiang, Shijian Lu:
Open-Vocabulary Object Detection via Language Hierarchy. - Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan:
Tolerant Algorithms for Learning with Arbitrary Covariate Shift. - Alessandro Stolfo, Ben Wu, Wes Gurnee, Yonatan Belinkov, Xingyi Song, Mrinmaya Sachan, Neel Nanda:
Confidence Regulation Neurons in Language Models. - Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arróyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation. - Runhao Shi, Jiaxi Ying, Daniel P. Palomar:
Adaptive Passive-Aggressive Framework for Online Regression with Side Information. - Yang Xu, Yifan Feng, Jun Zhang, Jun-Hai Yong, Yue Gao:
Assembly Fuzzy Representation on Hypergraph for Open-Set 3D Object Retrieval. - Kailu Wu, Fangfu Liu, Zhihan Cai, Runjie Yan, Hanyang Wang, Yating Hu, Yueqi Duan, Kaisheng Ma:
Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image. - Elias Nehme, Rotem Mulayoff, Tomer Michaeli:
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees. - Brian Hu Zhang, Ioannis Anagnostides, Gabriele Farina, Tuomas Sandholm:
Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games. - Laurent Bonnasse-Gahot, Christophe Pallier:
fMRI predictors based on language models of increasing complexity recover brain left lateralization. - Jifan Zhang, Lalit Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy T. Rogers, Kevin G. Jamieson, Bob Mankoff, Robert Nowak:
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning. - Xincheng Yao, Zixin Chen, Chao Gao, Guangtao Zhai, Chongyang Zhang:
ResAD: A Simple Framework for Class Generalizable Anomaly Detection. - Saehyung Lee, Jisoo Mok, Sangha Park, Yongho Shin, Dahuin Jung, Sungroh Yoon:
Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection. - Nicholas Gao, Stephan Günnemann:
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations. - Nimrah Mustafa, Rebekka Burkholz:
Dynamic Rescaling for Training GNNs. - Dongwoo Lee, JoonKyu Park, Kyoung Mu Lee:
GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring. - Alexandra Souly, Qingyuan Lu, Dillon Bowen, Tu Trinh, Elvis Hsieh, Sana Pandey, Pieter Abbeel, Justin Svegliato, Scott Emmons, Olivia Watkins, Sam Toyer:
A StrongREJECT for Empty Jailbreaks. - Tianhong Li, Dina Katabi, Kaiming He:
Return of Unconditional Generation: A Self-supervised Representation Generation Method. - Xiaosong Yuan, Chen Shen, Shaotian Yan, Xiaofeng Zhang, Liang Xie, Wenxiao Wang, Renchu Guan, Ying Wang, Jieping Ye:
Instance-adaptive Zero-shot Chain-of-Thought Prompting. - Luca Eyring, Shyamgopal Karthik, Karsten Roth, Alexey Dosovitskiy, Zeynep Akata:
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization. - Homaira Huda Shomee, Zhu Wang, Sathya N. Ravi, Sourav Medya:
IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design Patents. - Fengyu Gao, Ruiquan Huang, Jing Yang:
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups. - Chaoqi Chen, Luyao Tang, Hui Huang:
Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity. - Yuzhe Ji, Yijie Chen, Liuqing Yang, Rui Ding, Meng Yang, Xinhu Zheng:
VeXKD: The Versatile Integration of Cross-Modal Fusion and Knowledge Distillation for 3D Perception. - Pusen Dong, Tianchen Zhu, Yue Qiu, Haoyi Zhou, Jianxin Li:
From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning. - Tao Lin, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen, Yang Liu:
User-Creator Feature Polarization in Recommender Systems with Dual Influence. - Kristjan H. Greenewald, Yuancheng Yu, Hao Wang, Kai Xu:
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training. - Reza Ghane, Danil Akhtiamov, Babak Hassibi:
Universality in Transfer Learning for Linear Models. - Marvin Alberts, Oliver Schilter, Federico Zipoli, Nina Hartrampf, Teodoro Laino:
Unraveling Molecular Structure: A Multimodal Spectroscopic Dataset for Chemistry. - Yulia Rubanova, Tatiana Lopez-Guevara, Kelsey R. Allen, Will Whitney, Kimberly L. Stachenfeld, Tobias Pfaff:
Learning rigid-body simulators over implicit shapes for large-scale scenes and vision. - Ioannis Anagnostides, Tuomas Sandholm:
Convergence of $\text{log}(1/\epsilon)$ for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis. - Yanqin Jiang, Chaohui Yu, Chenjie Cao, Fan Wang, Weiming Hu, Jin Gao:
Animate3D: Animating Any 3D Model with Multi-view Video Diffusion. - Zijie Ye, Jia-Wei Liu, Jia Jia, Shikun Sun, Mike Zheng Shou:
Skinned Motion Retargeting with Dense Geometric Interaction Perception. - Alireza Fallah, Michael I. Jordan, Annie Ulichney:
Fair Allocation in Dynamic Mechanism Design. - Asma Ghandeharioun, Ann Yuan, Marius Guerard, Emily Reif, Michael A. Lepori, Lucas Dixon:
Who's asking? User personas and the mechanics of latent misalignment. - Jinliang Zheng, Jianxiong Li, Sijie Cheng, Yinan Zheng, Jiaming Li, Jihao Liu, Yu Liu, Jingjing Liu, Xianyuan Zhan:
Instruction-Guided Visual Masking. - Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng:
SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures. - Stephen Pasteris, Alberto Rumi, Maximilian Thiessen, Shota Saito, Atsushi Miyauchi, Fabio Vitale, Mark Herbster:
Bandits with Abstention under Expert Advice. - Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet:
Improved Algorithms for Contextual Dynamic Pricing. - Jian Guan, Wei Wu, Zujie Wen, Peng Xu, Hongning Wang, Minlie Huang:
AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback. - Hao Chen, Yujin Han, Diganta Misra, Xiang Li, Kai Hu, Difan Zou, Masashi Sugiyama, Jindong Wang, Bhiksha Raj:
Slight Corruption in Pre-training Data Makes Better Diffusion Models. - Rafael Rafailov, Yaswanth Chittepu, Ryan Park, Harshit Sikchi, Joey Hejna, W. Bradley Knox, Chelsea Finn, Scott Niekum:
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. - Yihao Zhang, Zeming Wei, Jun Sun, Meng Sun:
Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models. - Xiaomeng Hu, Pin-Yu Chen, Tsung-Yi Ho:
Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes. - Gen Li, Yuling Yan:
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models. - Boyi Zeng, Lizheng Wang, Yuncong Hu, Yi Xu, Chenghu Zhou, Xinbing Wang, Yu Yu, Zhouhan Lin:
HuRef: HUman-REadable Fingerprint for Large Language Models. - Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli:
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning. - George Andriopoulos, Zixuan Dong, Li Guo, Zifan Zhao, Keith W. Ross:
The Prevalence of Neural Collapse in Neural Multivariate Regression. - Yue Li, Yi Sun, Shida Sun, Juntian Ye, Yueyi Zhang, Feihu Xu, Zhiwei Xiong:
Toward Dynamic Non-Line-of-Sight Imaging with Mamba Enforced Temporal Consistency. - Moses Charikar, Chirag Pabbaraju, Kirankumar Shiragur:
Quantifying the Gain in Weak-to-Strong Generalization. - Edward Vendrow, Omiros Pantazis, Alexander Shepard, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha, Sara Beery, Grant Van Horn:
INQUIRE: A Natural World Text-to-Image Retrieval Benchmark. - Pengyu Cheng, Tianhao Hu, Han Xu, Zhisong Zhang, Yong Dai, Lei Han, Nan Du, Xiaolong Li:
Self-playing Adversarial Language Game Enhances LLM Reasoning. - Shishir G. Patil, Tianjun Zhang, Xin Wang, Joseph E. Gonzalez:
Gorilla: Large Language Model Connected with Massive APIs. - Hao Yan, Keith Levin:
Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models. - Jing-Cheng Pang, Si-Hang Yang, Kaiyuan Li, Jiaji Zhang, Xiong-Hui Chen, Nan Tang, Yang Yu:
KALM: Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts. - Lukás Picek, Christophe Botella, Maximilien Servajean, César Leblanc, Rémi Palard, Théo Larcher, Benjamin Deneu, Diego Marcos, Pierre Bonnet, Alexis Joly:
GeoPlant: Spatial Plant Species Prediction Dataset. - Yu-An Lin, Chen-Tao Lee, Chih-Han Yang, Guan-Ting Liu, Shao-Hua Sun:
Hierarchical Programmatic Option Framework. - Yingjun Du, Wenfang Sun, Cees Snoek:
IPO: Interpretable Prompt Optimization for Vision-Language Models. - Luis Müller, Daniel Kusuma, Blai Bonet, Christopher Morris:
Towards Principled Graph Transformers. - Alexander Modell:
Entrywise error bounds for low-rank approximations of kernel matrices. - Ruosen Li, Zimu Wang, Son Quoc Tran, Lei Xia, Xinya Du:
MEQA: A Benchmark for Multi-hop Event-centric Question Answering with Explanations. - Boyu Han, Qianqian Xu, Zhiyong Yang, Shilong Bao, Peisong Wen, Yangbangyan Jiang, Qingming Huang:
AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation. - Marvin Schmitt, Valentin Pratz, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev:
Consistency Models for Scalable and Fast Simulation-Based Inference. - Trevor Campbell:
General bounds on the quality of Bayesian coresets. - Lei Tan, Yukang Zhang, Keke Han, Pingyang Dai, Yan Zhang, Yongjian Wu, Rongrong Ji:
RLE: A Unified Perspective of Data Augmentation for Cross-Spectral Re-Identification. - Sike Wang, Pan Zhou, Jia Li, Hua Huang:
4-bit Shampoo for Memory-Efficient Network Training. - Jintang Li, Ruofan Wu, Xinzhou Jin, Boqun Ma, Liang Chen, Zibin Zheng:
State Space Models on Temporal Graphs: A First-Principles Study. - Benjamin Estermann, Luca A. Lanzendörfer, Yannick Niedermayr, Roger Wattenhofer:
PUZZLES: A Benchmark for Neural Algorithmic Reasoning. - Fengpeng Li, Kemou Li, Haiwei Wu, Jinyu Tian, Jiantao Zhou:
DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain. - Shirley Wu, Shiyu Zhao, Michihiro Yasunaga, Kexin Huang, Kaidi Cao, Qian Huang, Vassilis N. Ioannidis, Karthik Subbian, James Y. Zou, Jure Leskovec:
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases. - Tinglin Huang, Zhenqiao Song, Rex Ying, Wengong Jin:
Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer. - Dongchen Han, Ziyi Wang, Zhuofan Xia, Yizeng Han, Yifan Pu, Chunjiang Ge, Jun Song, Shiji Song, Bo Zheng, Gao Huang:
Demystify Mamba in Vision: A Linear Attention Perspective. - Ruihong Yin, Vladimir Yugay, Yue Li, Sezer Karaoglu, Theo Gevers:
FewViewGS: Gaussian Splatting with Few View Matching and Multi-stage Training. - Nicola Muca Cirone, Antonio Orvieto, Benjamin Walker, Cristopher Salvi, Terry J. Lyons:
Theoretical Foundations of Deep Selective State-Space Models. - Yinzhu Jin, Aman Shrivastava, Tom Fletcher:
Learning Group Actions on Latent Representations. - Haiyu Zhao, Lei Tian, Xinyan Xiao, Peng Hu, Yuanbiao Gou, Xi Peng:
AverNet: All-in-one Video Restoration for Time-varying Unknown Degradations. - Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszar, Bernhard Schölkopf:
Do Finetti: On Causal Effects for Exchangeable Data. - Ruizhi Liu, Zhisheng Zeng, Shizhe Ding, Jingyan Sui, Xingquan Li, Dongbo Bu:
NeuralSteiner: Learning Steiner Tree for Overflow-avoiding Global Routing in Chip Design. - Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu:
Contextual Bilevel Reinforcement Learning for Incentive Alignment. - Tian Xie, Xueru Zhang:
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions. - Yifei Wang, Kaiwen Hu, Sharut Gupta, Ziyu Ye, Yisen Wang, Stefanie Jegelka:
Understanding the Role of Equivariance in Self-supervised Learning. - Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani:
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models. - Oryan Yehezkel, Alon Zolfi, Amit Baras, Yuval Elovici, Asaf Shabtai:
DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms. - Chris Dongjoo Kim, Sangwoo Moon, Jihwan Moon, Dongyeon Woo, Gunhee Kim:
Sample Selection via Contrastive Fragmentation for Noisy Label Regression. - Salva Rühling Cachay, Brian Henn, Oliver Watt-Meyer, Christopher S. Bretherton, Rose Yu:
Probablistic Emulation of a Global Climate Model with Spherical DYffusion. - Neel Guha, Mayee F. Chen, Trevor Chow, Ishan S. Khare, Christopher Ré:
Smoothie: Label Free Language Model Routing. - Anton Antonov, Andrey Moskalenko, Denis Shepelev, Alexander Krapukhin, Konstantin Soshin, Anton Konushin, Vlad Shakhuro:
RClicks: Realistic Click Simulation for Benchmarking Interactive Segmentation. - Jiacong Hu, Jing Gao, Jingwen Ye, Yang Gao, Xingen Wang, Zunlei Feng, Mingli Song:
Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks. - Ning-Hsu (Albert) Wang, Yu-Lun Liu:
Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation. - Jongmin Lee, Minsu Cho:
3D Equivariant Pose Regression via Direct Wigner-D Harmonics Prediction. - Subash Timilsina, Sagar Shrestha, Xiao Fu:
Identifiable Shared Component Analysis of Unpaired Multimodal Mixtures. - Mahdi Morafah, Vyacheslav Kungurtsev, Hojin Chang, Chen Chen, Bill Lin:
Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration. - Fuming You, Minghui Fang, Li Tang, Rongjie Huang, Yongqi Wang, Zhou Zhao:
MoMu-Diffusion: On Learning Long-Term Motion-Music Synchronization and Correspondence. - Sam Griesemer, Defu Cao, Zijun Cui, Carolina Osorio, Yan Liu:
Active Sequential Posterior Estimation for Sample-Efficient Simulation-Based Inference. - Wesley Chung, Lynn Cherif, Doina Precup, David Meger:
Parseval Regularization for Continual Reinforcement Learning. - Lu Bai, Zhuo Xu, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock:
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning. - Zekun Cai, Guangji Bai, Renhe Jiang, Xuan Song, Liang Zhao:
Continuous Temporal Domain Generalization. - Robert J. Wang, Aseem Baranwal, Kimon Fountoulakis:
Analysis of Corrected Graph Convolutions. - Simone Foti, Stefanos Zafeiriou, Tolga Birdal:
UV-free Texture Generation with Denoising and Geodesic Heat Diffusion. - Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang:
A Theoretical Perspective for Speculative Decoding Algorithm. - Yongqi Wang, Wenxiang Guo, Rongjie Huang, Jiawei Huang, Zehan Wang, Fuming You, Ruiqi Li, Zhou Zhao:
Frieren: Efficient Video-to-Audio Generation Network with Rectified Flow Matching. - Haiqian Han, Jianing Li, Henglu Wei, Xiangyang Ji:
Event-3DGS: Event-based 3D Reconstruction Using 3D Gaussian Splatting. - Dvir Samuel, Rami Ben-Ari, Matan Levy, Nir Darshan, Gal Chechik:
Where's Waldo: Diffusion Features For Personalized Segmentation and Retrieval. - Ya-Wei Eileen Lin, Ronen Talmon, Ron Levie:
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters. - Jianrong Ding, Zhanyu Liu, Guanjie Zheng, Haiming Jin, Linghe Kong:
CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting. - Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr, Milad Nasr:
Query-Based Adversarial Prompt Generation. - Easton K. Huch, Jieru Shi, Madeline R. Abbott, Jessica R. Golbus, Alexander Moreno, Walter Dempsey:
RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions. - Brandon McMahan, Zhenghao Mark Peng, Bolei Zhou, Jonathan C. Kao:
Shared Autonomy with IDA: Interventional Diffusion Assistance. - Tengjie Zhu, Zhuo Chen, Jingnan Gao, Yichao Yan, Xiaokang Yang:
Multi-times Monte Carlo Rendering for Inter-reflection Reconstruction. - Zhenyu Wang, Aoxue Li, Zhenguo Li, Xihui Liu:
GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing. - Yifan Zhang, Junhui Hou:
Fine-grained Image-to-LiDAR Contrastive Distillation with Visual Foundation Models. - Yuxuan Li, Xiang Li, Weijie Li, Qibin Hou, Li Liu, Ming-Ming Cheng, Jian Yang:
SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection. - Zijian Gao, Xingxing Zhang, Kele Xu, Xinjun Mao, Huaimin Wang:
Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks. - Zih-Syuan Huang, Ching-pei Lee:
Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network. - Harvineet Singh, Fan Xia, Adarsh Subbaswamy, Alexej Gossmann, Jean Feng:
A hierarchical decomposition for explaining ML performance discrepancies. - Anushrut Jignasu, Kelly O. Marshall, Ankush Kumar Mishra, Lucas Nerone Rillo, Baskar Ganapathysubramanian, Aditya Balu, Chinmay Hegde, Adarsh Krishnamurthy:
Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing. - Cheikh Ahmed, Alexandre Forel, Axel Parmentier, Thibaut Vidal:
DistrictNet: Decision-aware learning for geographical districting. - Raef Bassily, Cristóbal Guzmán, Michael Menart:
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry. - Jian Luo, Jie Wang, Hong Wang, Huanshuo Dong, Zijie Geng, Hanzhu Chen, Yufei Kuang:
Neural Krylov Iteration for Accelerating Linear System Solving. - Linyi Li, Shijie Geng, Zhenwen Li, Yibo He, Hao Yu, Ziyue Hua, Guanghan Ning, Siwei Wang, Tao Xie, Hongxia Yang:
InfiBench: Evaluating the Question-Answering Capabilities of Code Large Language Models. - Nam Phuong Tran, The-Anh Ta, Debmalya Mandal, Long Tran-Thanh:
Symmetric Linear Bandits with Hidden Symmetry. - Da Yin, Haoyi Qiu, Kung-Hsiang Huang, Kai-Wei Chang, Nanyun Peng:
SafeWorld: Geo-Diverse Safety Alignment. - Nimita Shinde, Tianjiao Ding, Daniel P. Robinson, René Vidal:
Geometric Analysis of Nonlinear Manifold Clustering. - Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stärk, Stephan Thaler, Dominique Beaini:
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation. - Shikuang Deng, Yuhang Wu, Kangrui Du, Shi Gu:
Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks. - Philipp Froehlich, Heinz Koeppl:
Graph Structure Inference with BAM: Neural Dependency Processing via Bilinear Attention. - Bo Cheng, Yuhang Ma, Liebucha Wu, Shanyuan Liu, Ao Ma, Xiaoyu Wu, Dawei Leng, Yuhui Yin:
HiCo: Hierarchical Controllable Diffusion Model for Layout-to-image Generation. - Kuan Heng Lin, Sicheng Mo, Ben Klingher, Fangzhou Mu, Bolei Zhou:
Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance. - Qihang Yu, Mark Weber, Xueqing Deng, Xiaohui Shen, Daniel Cremers, Liang-Chieh Chen:
An Image is Worth 32 Tokens for Reconstruction and Generation. - Yunlong Hou, Vincent Y. F. Tan, Zixin Zhong:
Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits. - Alexander V. Nikitin, Letizia Iannucci, Samuel Kaski:
TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series. - Matteo Farina, Gianni Franchi, Giovanni Iacca, Massimiliano Mancini, Elisa Ricci:
Frustratingly Easy Test-Time Adaptation of Vision-Language Models. - Guanxiong Luo, Shoujin Huang, Martin Uecker:
Autoregressive Image Diffusion: Generation of Image Sequence and Application in MRI. - Chang Liu, Xiwei Wu, Yuan Feng, Qinxiang Cao, Junchi Yan:
Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation. - Saurav Jha, Dong Gong, Lina Yao:
CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models. - Suhan Cui, Prasenjit Mitra:
Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records. - Mijeong Kim, Jongwoo Lim, Bohyung Han:
4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization. - Sai Wang, Yutian Lin, Yu Wu, Bo Du:
Toward Real Ultra Image Segmentation: Leveraging Surrounding Context to Cultivate General Segmentation Model. - Hao Dong, Yue Zhao, Eleni N. Chatzi, Olga Fink:
MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities. - Salim I. Amoukou, Tom Bewley, Saumitra Mishra, Freddy Lécué, Daniele Magazzeni, Manuela Veloso:
Sequential Harmful Shift Detection Without Labels. - Shihan Ma, Bo Hu, Tianyu Jia, Alexander Kenneth Clarke, Blanka Zicher, Arnault H. Caillet, Dario Farina, José C. Príncipe:
Learning Cortico-Muscular Dependence through Orthonormal Decomposition of Density Ratios. - Xi Chen, Chuan Qin, Chuyu Fang, Chao Wang, Chen Zhu, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong:
Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking. - Liang-Hsuan Tseng, En-Pei Hu, Cheng-Han Chiang, Yuan Tseng, Hung-yi Lee, Lin-Shan Lee, Shao-Hua Sun:
REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR. - Yuan Deng, Jieming Mao, Vahab Mirrokni, Hanrui Zhang, Song Zuo:
Autobidder's Dilemma: Why More Sophisticated Autobidders Lead to Worse Auction Efficiency. - David Berghaus, Kostadin Cvejoski, Patrick Seifner, César Ali Marin Ojeda, Ramsés J. Sánchez:
Foundation Inference Models for Markov Jump Processes. - Eleni Straitouri, Suhas Thejaswi, Manuel Rodriguez:
Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets. - Lingxiao Li, Kaixiong Gong, Weihong Li, Xili Dai, Tao Chen, Xiaojun Yuan, Xiangyu Yue:
Bifröst: 3D-Aware Image Compositing with Language Instructions. - Mulin Yu, Tao Lu, Linning Xu, Lihan Jiang, Yuanbo Xiangli, Bo Dai:
GSDF: 3DGS Meets SDF for Improved Neural Rendering and Reconstruction. - Zhuoming Chen, Avner May, Ruslan Svirschevski, Yuhsun Huang, Max Ryabinin, Zhihao Jia, Beidi Chen:
Sequoia: Scalable and Robust Speculative Decoding. - Zohar Barak, Anupam Gupta, Inbal Talgam-Cohen:
MAC Advice for facility location mechanism design. - Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran:
Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs. - Lijie Hu, Songning Lai, Wenshuo Chen, Hongru Xiao, Hongbin Lin, Lu Yu, Jingfeng Zhang, Di Wang:
Towards Multi-dimensional Explanation Alignment for Medical Classification. - Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, Rui Melo, Gabriel Hautreux, Etienne Malaboeuf, Johanne Charpentier, Dominic Culver, Michael Desa:
SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain. - Cem Anil, Esin Durmus, Nina Panickssery, Mrinank Sharma, Joe Benton, Sandipan Kundu, Joshua Batson, Meg Tong, Jesse Mu, Daniel Ford, Francesco Mosconi, Rajashree Agrawal, Rylan Schaeffer, Naomi Bashkansky, Samuel Svenningsen, Mike Lambert, Ansh Radhakrishnan, Carson Denison, Evan Hubinger, Yuntao Bai, Trenton Bricken, Timothy Maxwell, Nicholas Schiefer, James Sully, Alex Tamkin, Tamera Lanham, Karina Nguyen, Tomek Korbak, Jared Kaplan, Deep Ganguli, Samuel R. Bowman, Ethan Perez, Roger B. Grosse, David Kristjanson Duvenaud:
Many-shot Jailbreaking. - Emanuele Zangrando, Steffen Schotthöfer, Gianluca Ceruti, Jonas Kusch, Francesco Tudisco:
Geometry-aware training of factorized layers in tensor Tucker format. - Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting. - Metod Jazbec, Alexander Timans, Tin Hadzi Veljkovic, Kaspar Sakmann, Dan Zhang, Christian Andersson Naesseth, Eric T. Nalisnick:
Fast yet Safe: Early-Exiting with Risk Control. - Han-Dong Lim, Donghwan Lee:
Regularized Q-Learning. - David Rügamer, Bernard X. W. Liew, Zainab Altai, Almond Stöcker:
A Functional Extension of Semi-Structured Networks. - Zihao Tang, Yixuan Qiu:
Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport. - Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He:
β-DPO: Direct Preference Optimization with Dynamic β. - Zhixiong Nan, Yilong Chen, Tianfei Zhou, Tao Xiang:
On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidance. - Yanhao Zhang, Zhihan Zhu, Yong Xia:
Block Sparse Bayesian Learning: A Diversified Scheme. - Puning Zhao, Lifeng Lai, Li Shen, Qingming Li, Jiafei Wu, Zhe Liu:
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy. - Jiahua Dong, Wenqi Liang, Hongliu Li, Duzhen Zhang, Meng Cao, Henghui Ding, Salman H. Khan, Fahad Shahbaz Khan:
How to Continually Adapt Text-to-Image Diffusion Models for Flexible Customization? - Dong Li, Aijia Zhang, Junqi Gao, Biqing Qi:
An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning. - Jihoon Tack, Jaehyung Kim, Eric Mitchell, Jinwoo Shin, Yee Whye Teh, Jonathan Richard Schwarz:
Online Adaptation of Language Models with a Memory of Amortized Contexts. - Subham S. Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T. Chiu, Alexander Rush, Volodymyr Kuleshov:
Simple and Effective Masked Diffusion Language Models. - Zhaorun Chen, Zhen Xiang, Chaowei Xiao, Dawn Song, Bo Li:
AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases. - Xiaoxia Cheng, Zeqi Tan, Wei Xue, Weiming Lu:
Information Re-Organization Improves Reasoning in Large Language Models. - Marius Potfer, Dorian Baudry, Hugo Richard, Vianney Perchet, Cheng Wan:
Improved learning rates in multi-unit uniform price auctions. - Sebastian Prillo, Wilson Wu, Yun Song:
Ultrafast classical phylogenetic method beats large protein language models on variant effect prediction. - Jiahe Huang, Guandao Yang, Zichen Wang, Jeong Joon Park:
DiffusionPDE: Generative PDE-Solving under Partial Observation. - Maximilian Muschalik, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara Hammer, Eyke Hüllermeier:
shapiq: Shapley Interactions for Machine Learning. - Yanghao Xiao, Haoxuan Li, Yongqiang Tang, Wensheng Zhang:
Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation. - Le-Trung Nguyen, Aël Quélennec, Enzo Tartaglione, Samuel Tardieu, Van-Tam Nguyen:
Activation Map Compression through Tensor Decomposition for Deep Learning. - Siyan Zhao, Tung Nguyen, Aditya Grover:
Probing the Decision Boundaries of In-context Learning in Large Language Models. - Luca Zancato, Arjun Seshadri, Yonatan Dukler, Aditya Golatkar, Yantao Shen, Benjamin Bowman, Matthew Trager, Alessandro Achille, Stefano Soatto:
B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory. - Branislav Kveton, Boris Oreshkin, Youngsuk Park, Aniket Deshmukh, Rui Song:
Online Posterior Sampling with a Diffusion Prior. - Yu-Ang Cheng, Ivan F. Rodriguez Rodriguez, Sixuan Chen, Kohitij Kar, Takeo Watanabe, Thomas Serre:
RTify: Aligning Deep Neural Networks with Human Behavioral Decisions. - Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng:
Transductive Learning is Compact. - Mason Hargrave, Alex Spaeth, Logan Grosenick:
EpiCare: A Reinforcement Learning Benchmark for Dynamic Treatment Regimes. - Zangir Iklassov, Yali Du, Farkhad Akimov, Martin Takác:
Self-Guiding Exploration for Combinatorial Problems. - Zheyi Fan, Wenyu Wang, Szu Hui Ng, Qingpei Hu:
Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization. - Jialin Chen, Jan Eric Lenssen, Aosong Feng, Weihua Hu, Matthias Fey, Leandros Tassiulas, Jure Leskovec, Rex Ying:
From Similarity to Superiority: Channel Clustering for Time Series Forecasting. - Zhenning Shi, Haoshuai Zheng, Chen Xu, Changsheng Dong, Bin Pan, Xueshuo Xie, Along He, Tao Li, Huazhu Fu:
Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual Noise. - Weitong Zhang, Zhiyuan Fan, Jiafan He, Quanquan Gu:
Achieving Constant Regret in Linear Markov Decision Processes. - Weihao Yuan, Yisheng He, Weichao Shen, Yuan Dong, Xiaodong Gu, Zilong Dong, Liefeng Bo, Qixing Huang:
MoGenTS: Motion Generation based on Spatial-Temporal Joint Modeling. - Daniel Beaglehole, Peter Súkeník, Marco Mondelli, Misha Belkin:
Average gradient outer product as a mechanism for deep neural collapse. - Liang Peng, Junyuan Gao, Xinran Liu, Weihong Li, Shaohua Dong, Zhipeng Zhang, Heng Fan, Libo Zhang:
VastTrack: Vast Category Visual Object Tracking. - Fangzhao Zhang, Mert Pilanci:
Spectral Adapter: Fine-Tuning in Spectral Space. - Mustafa Shukor, Matthieu Cord:
Implicit Multimodal Alignment: On the Generalization of Frozen LLMs to Multimodal Inputs. - Sk Miraj Ahmed, Fahim Faisal Niloy, Xiangyu Chang, Dripta S. Raychaudhuri, Samet Oymak, Amit K. Roy-Chowdhury:
CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions. - Loka Li, Haoyue Dai, Hanin Al Ghothani, Biwei Huang, Jiji Zhang, Shahar Harel, Isaac Bentwich, Guangyi Chen, Kun Zhang:
On Causal Discovery in the Presence of Deterministic Relations. - Charles Guille-Escuret, Pierre-André Noël, Ioannis Mitliagkas, David Vázquez, João Monteiro:
Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection. - Jiwan Hur, Dong-Jae Lee, Gyojin Han, Jaehyun Choi, Yunho Jeon, Junmo Kim:
Unlocking the Capabilities of Masked Generative Models for Image Synthesis via Self-Guidance. - Pranjal Aggarwal, Aman Madaan, Ankit Anand, Srividya Pranavi Potharaju, Swaroop Mishra, Pei Zhou, Aditya Gupta, Dheeraj Rajagopal, Karthik Kappaganthu, Yiming Yang, Shyam Upadhyay, Manaal Faruqui, Mausam:
AutoMix: Automatically Mixing Language Models. - M. Maruf, Arka Daw, Kazi Sajeed Mehrab, Harish Babu Manogaran, Abhilash Neog, Medha Sawhney, Mridul Khurana, James P. Balhoff, Yasin Bakis, Bahadir Altintas, Matthew J. Thompson, Elizabeth G. Campolongo, Josef C. Uyeda, Hilmar Lapp, Henry L. Bart Jr., Paula M. Mabee, Yu Su, Wei-Lun Chao, Charles V. Stewart, Tanya Y. Berger-Wolf, Wasila M. Dahdul, Anuj Karpatne:
VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images. - Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, Ohsung Kwon, Soyoon Kim, Jungwhan Kim, Jaehong Lee, Eunwoo Song, Myungwoo Oh, Jung-Woo Ha, Sungroh Yoon, Kang Min Yoo:
Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation. - Matt Jones, Peter G. Chang, Kevin P. Murphy:
Bayesian Online Natural Gradient (BONG). - Wassim Gabriel, Omar Shouman, Eva Ayla Schröder, Florian Bößl, Mathias Wilhelm:
PROSPECT PTMs: Rich Labeled Tandem Mass Spectrometry Dataset of Modified Peptides for Machine Learning in Proteomics. - Jiachen T. Wang, Tong Wu, Dawn Song, Prateek Mittal, Ruoxi Jia:
GREATS: Online Selection of High-Quality Data for LLM Training in Every Iteration. - Jiachen Li, Xinyao Wang, Sijie Zhu, Chia-Wen Kuo, Lu Xu, Fan Chen, Jitesh Jain, Humphrey Shi, Longyin Wen:
CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts. - Amit Bracha, Thomas Dagès, Ron Kimmel:
Wormhole Loss for Partial Shape Matching. - Le Zhuo, Ruoyi Du, Han Xiao, Yangguang Li, Dongyang Liu, Rongjie Huang, Wenze Liu, Xiangyang Zhu, Fu-Yun Wang, Zhanyu Ma, Xu Luo, Zehan Wang, Kaipeng Zhang, Lirui Zhao, Si Liu, Xiangyu Yue, Wanli Ouyang, Yu Qiao, Hongsheng Li, Peng Gao:
Lumina-Next : Making Lumina-T2X Stronger and Faster with Next-DiT. - Yikai Wang, Xinzhou Wang, Zilong Chen, Zhengyi Wang, Fuchun Sun, Jun Zhu:
Vidu4D: Single Generated Video to High-Fidelity 4D Reconstruction with Dynamic Gaussian Surfels. - Xiao Lin, Zhining Liu, Dongqi Fu, Ruizhong Qiu, Hanghang Tong:
BackTime: Backdoor Attacks on Multivariate Time Series Forecasting. - Yihe Deng, Pan Lu, Fan Yin, Ziniu Hu, Sheng Shen, Quanquan Gu, James Y. Zou, Kai-Wei Chang, Wei Wang:
Enhancing Large Vision Language Models with Self-Training on Image Comprehension. - Zirui Wang, Yue Deng, Junfeng Long, Yin Zhang:
Parallelizing Model-based Reinforcement Learning Over the Sequence Length. - Yu Lu, Yuanzhi Liang, Linchao Zhu, Yi Yang:
FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention. - Yongxu Zhang, Shreya Saxena:
Inference of Neural Dynamics Using Switching Recurrent Neural Networks. - Meenatchi Sundaram Muthu Selva Annamalai, Emiliano De Cristofaro:
Nearly Tight Black-Box Auditing of Differentially Private Machine Learning. - Michael A. Lepori, Alexa R. Tartaglini, Wai Keen Vong, Thomas Serre, Brenden M. Lake, Ellie Pavlick:
Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects. - Chengpeng Wang, Wuqi Zhang, Zian Su, Xiangzhe Xu, Xiaoheng Xie, Xiangyu Zhang:
LLMDFA: Analyzing Dataflow in Code with Large Language Models. - Wenjun Ke, Jiahao Wang, Peng Wang, Jiajun Liu, Dong Nie, Guozheng Li, Yining Li:
Unveiling LoRA Intrinsic Ranks via Salience Analysis. - Shuai He, Shuntian Zheng, Anlong Ming, Banyu Wu, Huadong Ma:
Rethinking No-reference Image Exposure Assessment from Holism to Pixel: Models, Datasets and Benchmarks. - Hanxin Zhu, Tianyu He, Anni Tang, Junliang Guo, Zhibo Chen, Jiang Bian:
Compositional 3D-aware Video Generation with LLM Director. - Jiwoong Park, Yang Shen:
Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation. - Chenrui Duan, Zelin Zang, Siyuan Li, Yongjie Xu, Stan Z. Li:
PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation. - Mohamed-Hicham Leghettas, Markus Püschel:
Learning Bregman Divergences with Application to Robustness. - Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang:
Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization. - Yuri R. Fonseca, Caio Peixoto, Yuri F. Saporito:
Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients. - Yushun Zhang, Congliang Chen, Tian Ding, Ziniu Li, Ruoyu Sun, Zhi-Quan Luo:
Why Transformers Need Adam: A Hessian Perspective. - Zachery Boner, Harry Chen, Lesia Semenova, Ronald Parr, Cynthia Rudin:
Using Noise to Infer Aspects of Simplicity Without Learning. - Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter:
Energy-based Hopfield Boosting for Out-of-Distribution Detection. - Yann N. Dauphin, Atish Agarwala, Hossein Mobahi:
Neglected Hessian component explains mysteries in sharpness regularization. - Tian Qin, Zhiwei Deng, David Alvarez-Melis:
A Label is Worth A Thousand Images in Dataset Distillation. - Jinyoung Park, Minseong Bae, Dohwan Ko, Hyunwoo J. Kim:
LLaMo: Large Language Model-based Molecular Graph Assistant. - Chengshuai Shi, Kun Yang, Jing Yang, Cong Shen:
Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models. - Yikun Miao, Meiqing Wu, Siew Kei Lam, Changsheng Li, Thambipillai Srikanthan:
Hierarchical Object-Aware Dual-Level Contrastive Learning for Domain Generalized Stereo Matching. - Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding:
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees. - Wenjun Miao, Guansong Pang, Jin Zheng, Xiao Bai:
Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation. - Yuanjie Shi, Subhankar Ghosh, Taha Belkhouja, Jana Doppa, Yan Yan:
Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration. - Zhicheng Chen, Shibo Feng, Zhong Zhang, Xi Xiao, Xingyu Gao, Peilin Zhao:
SDformer: Similarity-driven Discrete Transformer For Time Series Generation. - Yusen Zhang, Ruoxi Sun, Yanfei Chen, Tomas Pfister, Rui Zhang, Sercan Ö. Arik:
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks. - Guikun Chen, Jin Li, Wenguan Wang:
Scene Graph Generation with Role-Playing Large Language Models. - Xizhou Zhu, Xue Yang, Zhaokai Wang, Hao Li, Wenhan Dou, Junqi Ge, Lewei Lu, Yu Qiao, Jifeng Dai:
Parameter-Inverted Image Pyramid Networks. - Szymon Kobus, Tze-Yang Tung, Deniz Gündüz:
Universal Sample Coding. - Yikang Chen, Dehui Du, Lili Tian:
Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation. - Yihong Luo, Yuhan Chen, Siya Qiu, Yiwei Wang, Chen Zhang, Yan Zhou, Xiaochun Cao, Jing Tang:
Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification. - Guang Yang, Yuan Cao, Long Feng:
Attention boosted Individualized Regression. - Shuai Yuan, Guancong Lin, Lixian Zhang, Runmin Dong, Jinxiao Zhang, Shuang Chen, Juepeng Zheng, Jie Wang, Haohuan Fu:
FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding. - Ho Man Kwan, Ge Gao, Fan Zhang, Andrew Gower, David Bull:
NVRC: Neural Video Representation Compression. - Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Arash Vahdat, Weili Nie:
Molecule Generation with Fragment Retrieval Augmentation. - Xiaoxue Han, Zhuo Feng, Yue Ning:
A Topology-aware Graph Coarsening Framework for Continual Graph Learning. - Mustafa Chasmai, Alexander Shepard, Subhransu Maji, Grant Van Horn:
The iNaturalist Sounds Dataset. - Hossein Mirzaei, Ali Ansari, Bahar Dibaei Nia, Mojtaba Nafez, Moein Madadi, Sepehr Rezaee, Zeinab Taghavi, Arad Maleki, Kian Shamsaie, Mahdi Hajialilue, Jafar Habibi, Mohammad Sabokrou, Mohammad Hossein Rohban:
Scanning Trojaned Models Using Out-of-Distribution Samples. - Zhenyi Wang, Heng Huang:
Model Sensitivity Aware Continual Learning. - Yuan Gan, Jiaxu Miao, Yi Yang:
DataStealing: Steal Data from Diffusion Models in Federated Learning with Multiple Trojans. - Syamantak Kumar, Derek Bean, Peter J. Bickel, Purnamrita Sarkar:
Nonparametric Evaluation of Noisy ICA Solutions. - Diana Cai, Chirag Modi, Charles Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul:
EigenVI: score-based variational inference with orthogonal function expansions. - Shuaipeng Li, Penghao Zhao, Hailin Zhang, Xingwu Sun, Hao Wu, Dian Jiao, Weiyan Wang, Chengjun Liu, Zheng Fang, Jinbao Xue, Yangyu Tao, Bin Cui, Di Wang:
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling. - Qiuhao Zeng, Long-Kai Huang, Qi Chen, Charles X. Ling, Boyu Wang:
Towards Understanding Evolving Patterns in Sequential Data. - Mark Rowland, Kevin Kevin Li, Rémi Munos, Clare Lyle, Yunhao Tang, Will Dabney:
Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model. - Yating Xu, Chen Li, Gim Hee Lee:
MVSDet: Multi-View Indoor 3D Object Detection via Efficient Plane Sweeps. - Gokul Gowri, Xiao-Kang Lun, Allon M. Klein, Peng Yin:
Approximating mutual information of high-dimensional variables using learned representations. - Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi:
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. - Xinting Liao, Weiming Liu, Pengyang Zhou, Fengyuan Yu, Jiahe Xu, Jun Wang, Wenjie Wang, Chaochao Chen, Xiaolin Zheng:
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection. - Li Liu, Diji Yang, Sijia Zhong, Kalyana Suma Sree Tholeti, Lei Ding, Yi Zhang, Leilani Gilpin:
Right this way: Can VLMs Guide Us to See More to Answer Questions? - Clément L. Canonne, Joy Qiping Yang:
Entropy testing and its application to testing Bayesian networks. - Philip Amortila, Dylan J. Foster, Nan Jiang, Akshay Krishnamurthy, Zakaria Mhammedi:
Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity. - Linye Lyu, Jiawei Zhou, Daojing He, Yu Li:
CNCA: Toward Customizable and Natural Generation of Adversarial Camouflage for Vehicle Detectors. - Anh Bui, Tung-Long Vuong, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Q. Phung:
Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation. - Sujai Hiremath, Jacqueline R. M. A. Maasch, Mengxiao Gao, Promit Ghosal, Kyra Gan:
Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models. - Arian Prabowo, Xiachong Lin, Imran Razzak, Hao Xue, Emily W. Yap, Matthew Amos, Flora D. Salim:
Building Timeseries Dataset: Empowering Large-Scale Building Analytics. - Thomas Melistas, Nikos Spyrou, Nefeli Gkouti, Pedro Sanchez, Athanasios Vlontzos, Yannis Panagakis, Giorgos Papanastasiou, Sotirios A. Tsaftaris:
Benchmarking Counterfactual Image Generation. - Minghao Han, Shiyin Jiang, Shengxi Li, Xin Deng, Mai Xu, Ce Zhu, Shuhang Gu:
Causal Context Adjustment Loss for Learned Image Compression. - Claire Bizon Monroc, Ana Busic, Donatien Dubuc, Jiamin Zhu:
WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control. - Xinyin Ma, Gongfan Fang, Michael Bi Mi, Xinchao Wang:
Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching. - Xi Liu, Chaoyi Zhou, Siyu Huang:
3DGS-Enhancer: Enhancing Unbounded 3D Gaussian Splatting with View-consistent 2D Diffusion Priors. - Zirun Guo, Tao Jin, Jingyuan Chen, Zhou Zhao:
Classifier-guided Gradient Modulation for Enhanced Multimodal Learning. - Itai Gat, Tal Remez, Neta Shaul, Felix Kreuk, Ricky T. Q. Chen, Gabriel Synnaeve, Yossi Adi, Yaron Lipman:
Discrete Flow Matching. - Weiyu Ma, Qirui Mi, Yongcheng Zeng, Xue Yan, Runji Lin, Yuqiao Wu, Jun Wang, Haifeng Zhang:
Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach. - Giung Nam, Juho Lee:
Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems. - Václav Vorácek:
Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness. - Shangquan Sun, Wenqi Ren, Zikun Liu, Hyunhee Park, Rui Wang, Xiaochun Cao:
EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture Models. - Yichen Zhu, Zhicai Ou, Feifei Feng, Jian Tang:
Any2Policy: Learning Visuomotor Policy with Any-Modality. - Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba, Da-shan Shiu, Guillaume Hennequin, Alberto Bernacchia:
Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization. - Junho Kim, Hyunjun Kim, Yeonju Kim, Yong Man Ro:
CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models. - Junyan Liu, Yunfan Li, Ruosong Wang, Lin Yang:
Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning. - Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff:
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity. - Kai Liu, Zhihang Fu, Chao Chen, Wei Zhang, Rongxin Jiang, Fan Zhou, Yaowu Chen, Yue Wu, Jieping Ye:
Enhancing LLM's Cognition via Structurization. - Jian Qian, Haichen Hu, David Simchi-Levi:
Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff. - Gianluca Mancusi, Mattia Bernardi, Aniello Panariello, Angelo Porrello, Rita Cucchiara, Simone Calderara:
Is Multiple Object Tracking a Matter of Specialization? - Vishaal Udandarao, Karsten Roth, Sebastian Dziadzio, Ameya Prabhu, Mehdi Cherti, Oriol Vinyals, Olivier J. Hénaff, Samuel Albanie, Zeynep Akata, Matthias Bethge:
A Practitioner's Guide to Real-World Continual Multimodal Pretraining. - Abdullah Bin Jasni, Akiko Manada, Kohei Watabe:
DiffuPac: Contextual Mimicry in Adversarial Packets Generation via Diffusion Model. - Qihao Liu, Zhanpeng Zeng, Ju He, Qihang Yu, Xiaohui Shen, Liang-Chieh Chen:
Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models and Time-Dependent Layer Normalization. - Jeonghwan Lee, Cong Ma:
Off-policy estimation with adaptively collected data: the power of online learning. - Ziwei Li, Xiaoqi Wang, Hong-You Chen, Han-Wei Shen, Wei-Lun Chao:
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction. - Luis Cubillos, Guy Revach, Matthew Mender, Joseph T. Costello, Hisham Temmar, Aren Hite, Diksha Anoop Kumar Zutshi, Dylan Wallace, Xiaoyong Ni, Madison Kelberman, Matt S. Willsey, Ruud van Sloun, Nir Shlezinger, Parag G. Patil, Anne Draelos, Cynthia A. Chestek:
Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces. - Brian Zhang, Zhuo Zhang:
Detecting Bugs with Substantial Monetary Consequences by LLM and Rule-based Reasoning. - Ju-Sheng Hong, Junwen Yao, Jonas W. Mueller, Jane-Ling Wang:
SAND: Smooth imputation of sparse and noisy functional data with Transformer networks. - Saiyue Lyu, Shadab Shaikh, Frederick Shpilevskiy, Evan Shelhamer, Mathias Lécuyer:
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences. - Xinwang Chen, Ning Liu, Yichen Zhu, Feifei Feng, Jian Tang:
EDT: An Efficient Diffusion Transformer Framework Inspired by Human-like Sketching. - Vu C. Dinh, Lam S. Ho, Cuong V. Nguyen:
Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient. - Aref Miri Rekavandi, Farhad Farokhi, Olga Ohrimenko, Benjamin I. P. Rubinstein:
Certified Adversarial Robustness via Randomized α-Smoothing for Regression Models. - Xiaodong Wu, Wenyi Yu, Chao Zhang, Philip C. Woodland:
An Improved Empirical Fisher Approximation for Natural Gradient Descent. - Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui:
The Benefits of Balance: From Information Projections to Variance Reduction. - Seongwoong Cho, Donggyun Kim, Jinwoo Lee, Seunghoon Hong:
Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control. - Etienne Vareille, Michele Linardi, Ioannis Tsamardinos, Vassilis Christophides:
ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions. - Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang:
Kernel PCA for Out-of-Distribution Detection. - Sergio Calo, Anders Jonsson, Gergely Neu, Ludovic Schwartz, Javier Segovia-Aguas:
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently. - Yuchun Miao, Sen Zhang, Liang Ding, Rong Bao, Lefei Zhang, Dacheng Tao:
InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling. - Kunhe Yang, Hanrui Zhang:
Computational Aspects of Bayesian Persuasion under Approximate Best Response. - Yunqiao Yang, Long-Kai Huang, Shengzhuang Chen, Kede Ma, Ying Wei:
Learning Where to Edit Vision Transformers. - Patrick Tser Jern Kon, Jiachen Liu, Yiming Qiu, Weijun Fan, Ting He, Lei Lin, Haoran Zhang, Owen Park, George Elengikal, Yuxin Kang, Ang Chen, Mosharaf Chowdhury, Myungjin Lee, Xinyu Wang:
IaC-Eval: A Code Generation Benchmark for Cloud Infrastructure-as-Code Programs. - Xin Qiu, Risto Miikkulainen:
Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space. - Jerome Sieber, Carmen Amo Alonso, Alexandre Didier, Melanie N. Zeilinger, Antonio Orvieto:
Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks. - Benjamin Ellis, Matthew Thomas Jackson, Andrei Lupu, Alexander David Goldie, Mattie Fellows, Shimon Whiteson, Jakob N. Foerster:
Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps. - Xiaochen Ma, Xuekang Zhu, Lei Su, Bo Du, Zhuohang Jiang, Bingkui Tong, Zeyu Lei, Xinyu Yang, Chi-Man Pun, Jiancheng Lv, Jizhe Zhou:
IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localization. - Sumukh K. Aithal, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter:
Understanding Hallucinations in Diffusion Models through Mode Interpolation. - Haolin Liu, Zakaria Mhammedi, Chen-Yu Wei, Julian Zimmert:
Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback. - Zehui Li, Vallijah Subasri, Guy-Bart Stan, Yiren Zhao, Bo Wang:
GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning. - Kehan Guo, Bozhao Nan, Yujun Zhou, Taicheng Guo, Zhichun Guo, Mihir Surve, Zhenwen Liang, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang:
Can LLMs Solve Molecule Puzzles? A Multimodal Benchmark for Molecular Structure Elucidation. - Chenxi Zhao, Jinglei Shi, Liqiang Nie, Jufeng Yang:
To Err Like Human: Affective Bias-Inspired Measures for Visual Emotion Recognition Evaluation. - Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui:
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization. - Hoonhee Cho, Taewoo Kim, Yuhwan Jeong, Kuk-Jin Yoon:
A Benchmark Dataset for Event-Guided Human Pose Estimation and Tracking in Extreme Conditions. - Pei Xiao, Zizhen Zhang, Jinbiao Chen, Jiahai Wang, Zhenzhen Zhang:
Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times. - Bogdan Kulynych, Juan Felipe Gómez, Georgios Kaissis, Flávio P. Calmon, Carmela Troncoso:
Attack-Aware Noise Calibration for Differential Privacy. - Qi Tang, Yao Zhao, Meiqin Liu, Chao Yao:
SeeClear: Semantic Distillation Enhances Pixel Condensation for Video Super-Resolution. - Jesse Farebrother, Pablo Samuel Castro:
CALE: Continuous Arcade Learning Environment. - Tianyuan Jin, Yu Yang, Jing Tang, Xiaokui Xiao, Pan Xu:
Optimal Batched Best Arm Identification. - Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang:
Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration. - Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni:
Metric Flow Matching for Smooth Interpolations on the Data Manifold. - Xi Yang, Huanling Liu, De Cheng, Nannan Wang, Xinbo Gao:
Feature-Level Adversarial Attacks and Ranking Disruption for Visible-Infrared Person Re-identification. - An-Chieh Cheng, Hongxu Yin, Yang Fu, Qiushan Guo, Ruihan Yang, Jan Kautz, Xiaolong Wang, Sifei Liu:
SpatialRGPT: Grounded Spatial Reasoning in Vision-Language Models. - Xingyi Yang, Xinchao Wang:
Language Model as Visual Explainer. - Aoran Wang, Tsz Pan Tong, Andrzej Mizera, Jun Pang:
Benchmarking Structural Inference Methods for Interacting Dynamical Systems with Synthetic Data. - Chu Xin Cheng, Raul Astudillo, Thomas A. Desautels, Yisong Yue:
Practical Bayesian Algorithm Execution via Posterior Sampling. - Yiyan Huang, Cheuk Hang Leung, Siyi Wang, Yijun Li, Qi Wu:
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators. - Wei Tang, Haifeng Xu, Ruimin Zhang, Derek Zhu:
Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling. - Aayush Karan, Kulin Shah, Sitan Chen, Yonina C. Eldar:
Unrolled denoising networks provably learn to perform optimal Bayesian inference. - Jayden Teoh Jing Teoh, Wenjun Li, Pradeep Varakantham:
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design. - Eryn Sale, Wenhao Zhang:
The Bayesian sampling in a canonical recurrent circuit with a diversity of inhibitory interneurons. - Fangdi Wang, Jiaqi Jin, Jingtao Hu, Suyuan Liu, Xihong Yang, Siwei Wang, Xinwang Liu, En Zhu:
Evaluate then Cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering. - Omead Pooladzandi, Sunay Bhat, Jeffrey Jiang, Alexander Branch, Gregory J. Pottie:
PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics. - Haoxuan Li, Yue Liu, Zhi Geng, Kun Zhang:
A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs. - Tu Anh-Nguyen, Joey Huchette, Christian Tjandraatmadja:
Learning Generalized Linear Programming Value Functions. - Jiarui Jiang, Wei Huang, Miao Zhang, Taiji Suzuki, Liqiang Nie:
Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization. - Rohith Peddi, Shivvrat Arya, Bharath Challa, Likhitha Pallapothula, Akshay Vyas, Bhavya Gouripeddi, Qifan Zhang, Jikai Wang, Vasundhara Komaragiri, Eric D. Ragan, Nicholas Ruozzi, Yu Xiang, Vibhav Gogate:
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities. - Hui Xian Grace Lim, Xuanming Cui, Yogesh S. Rawat, Ser Nam Lim:
AirSketch: Generative Motion to Sketch. - Felipe Maia Polo, Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun:
Weak Supervision Performance Evaluation via Partial Identification. - Wen-Bo Du, Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou:
Avoiding Undesired Future with Minimal Cost in Non-Stationary Environments. - Mahmoud Ahmed, Xiang Li, Arpit Prajapati, Mohamed Elhoseiny:
3DCoMPaT200: Language Grounded Large-Scale 3D Vision Dataset for Compositional Recognition. - Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Alasdair Newson, Matthieu Cord:
A Concept-Based Explainability Framework for Large Multimodal Models. - Fanqi Kong, Yizhe Huang, Song-Chun Zhu, Siyuan Qi, Xue Feng:
Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games. - Zhangyang Gao, Jue Wang, Cheng Tan, Lirong Wu, Yufei Huang, Siyuan Li, Zhirui Ye, Stan Z. Li:
UniIF: Unified Molecule Inverse Folding. - Mingyang Zhou, Weiji Cao, Hao Liao, Rui Mao:
Motif-oriented influence maximization for viral marketing in large-scale social networks. - Dapeng Hu, Romy Luo, Jian Liang, Chuan Sheng Foo:
Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline. - Zhehao Zhang, Jiaao Chen, Diyi Yang:
DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph. - Tycho F. A. van der Ouderaa, Mark van der Wilk, Pim de Haan:
Noether's Razor: Learning Conserved Quantities. - Wayne Soo, Aldo Battista, Puria Radmard, Xiao-Jing Wang:
Recurrent neural network dynamical systems for biological vision. - Jacob M. Chen, Rohit Bhattacharya, Katherine A. Keith:
Proximal Causal Inference With Text Data. - Chu Zhou, Yixing Liu, Chao Xu, Boxin Shi:
Quality-Improved and Property-Preserved Polarimetric Imaging via Complementarily Fusing. - Andy Arditi, Oscar Obeso, Aaquib Syed, Daniel Paleka, Nina Panickssery, Wes Gurnee, Neel Nanda:
Refusal in Language Models Is Mediated by a Single Direction. - Zheda Mai, Arpita Chowdhury, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Fine-Tuning is Fine, if Calibrated. - Yiqing Lin, Jianheng Tang, Chenyi Zi, H. Vicky Zhao, Yuan Yao, Jia Li:
UniGAD: Unifying Multi-level Graph Anomaly Detection. - Jia-Wei Liu, Weijia Mao, Zhongcong Xu, Jussi Keppo, Mike Zheng Shou:
Exocentric-to-Egocentric Video Generation. - Fredrik D. Johansson:
IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark. - Tao Hu, Wenhang Ge, Yuyang Zhao, Gim Hee Lee:
X-Ray: A Sequential 3D Representation For Generation. - Pengcheng Jiang, Lang Cao, Cao (Danica) Xiao, Parminder Bhatia, Jimeng Sun, Jiawei Han:
KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World Knowledge. - Andi Zhang, Mingtian Zhang, Damon Wischik:
Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective. - Han Cheng Lie, Alexander Munteanu:
Data subsampling for Poisson regression with pth-root-link. - Yihong Guo, Yixuan Wang, Yuanyuan Shi, Pan Xu, Anqi Liu:
Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation. - Yonghan Jung, Alexis Bellot:
Efficient Policy Evaluation Across Multiple Different Experimental Datasets. - Xuyuan Liu, Yinghao Cai, Qihui Yang, Yujun Yan:
Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks. - Christian Schmid, James M. Murray:
Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron. - Naitik Khandelwal, Xiao Liu, Mengmi Zhang:
Adaptive Visual Scene Understanding: Incremental Scene Graph Generation. - Matteo Pagliardini, Amirkeivan Mohtashami, François Fleuret, Martin Jaggi:
DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging. - Bong Gyun Kang, Dongjun Lee, HyunGi Kim, Dohyun Chung, Sungroh Yoon:
Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting. - Teng Li, Liwen Zhang, Youcheng Zhang, ZijunHu, Pengcheng Pi, Zongqing Lu, Qingmin Liao, Zhe Ma:
AdaPKC: PeakConv with Adaptive Peak Receptive Field for Radar Semantic Segmentation. - Cong Wan, Yuhang He, Xiang Song, Yihong Gong:
Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models. - Benjamin Feuer, Jiawei Xu, Niv Cohen, Patrick Yubeaton, Govind Mittal, Chinmay Hegde:
SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image Classification. - Hao Zhang, Chenglin Li, Nuowen Kan, Ziyang Zheng, Wenrui Dai, Junni Zou, Hongkai Xiong:
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach. - Jieren Deng, Haojian Zhang, Kun Ding, Jianhua Hu, Xingxuan Zhang, Yunkuan Wang:
Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection. - Zhongchao Yi, Zhengyang Zhou, Qihe Huang, Yanjiang Chen, Liheng Yu, Xu Wang, Yang Wang:
Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning Framework. - Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang:
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance. - Junwei Deng, Ting-Wei Li, Shiyuan Zhang, Shixuan Liu, Yijun Pan, Hao Huang, Xinhe Wang, Pingbang Hu, Xingjian Zhang, Jiaqi W. Ma:
dattri: A Library for Efficient Data Attribution. - Ruijie Zhu, Ziqing Wang, Leilani Gilpin, Jason Eshraghian:
Autonomous Driving with Spiking Neural Networks. - Jia-Fong Yeh, Kuo-Han Hung, Pang-Chi Lo, Chi-Ming Chung, Tsung-Han Wu, Hung-Ting Su, Yi-Ting Chen, Winston H. Hsu:
AED: Adaptable Error Detection for Few-shot Imitation Policy. - Huy Hoang, Tien Mai, Pradeep Varakantham:
SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning. - Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra:
Aligning LLM Agents by Learning Latent Preference from User Edits. - Chufan Shi, Cheng Yang, Xinyu Zhu, Jiahao Wang, Taiqiang Wu, Siheng Li, Deng Cai, Yujiu Yang, Yu Meng:
Unchosen Experts Can Contribute Too: Unleashing MoE Models' Power by Self-Contrast. - Bobak T. Kiani, Lukas Fesser, Melanie Weber:
Unitary Convolutions for Learning on Graphs and Groups. - Yidong Ouyang, Liyan Xie, Hongyuan Zha, Guang Cheng:
Transfer Learning for Diffusion Models. - Marzi Heidari, Hanping Zhang, Yuhong Guo:
Reinforcement Learning Guided Semi-Supervised Learning. - Yangyang Yu, Zhiyuan Yao, Haohang Li, Zhiyang Deng, Yuechen Jiang, Yupeng Cao, Zhi Chen, Jordan W. Suchow, Zhenyu Cui, Rong Liu, Zhaozhuo Xu, Denghui Zhang, Koduvayur Subbalakshmi, Guojun Xiong, Yueru He, Jimin Huang, Dong Li, Qianqian Xie:
FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making. - Bharath Muppasani, Protik Nag, Vignesh Narayanan, Biplav Srivastava, Michael N. Huhns:
Towards Effective Planning Strategies for Dynamic Opinion Networks. - Jake Fawkes, Nic Fishman, Mel Andrews, Zachary C. Lipton:
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning. - Matthias Tangemann, Matthias Kümmerer, Matthias Bethge:
Object segmentation from common fate: Motion energy processing enables human-like zero-shot generalization to random dot stimuli. - Jiho Choi, Seonho Lee, Seungho Lee, Minhyun Lee, Hyunjung Shim:
Understanding Multi-Granularity for Open-Vocabulary Part Segmentation. - Bo-Ruei Huang, Chun-Kai Yang, Chun-Mao Lai, Dai-Jie Wu, Shao-Hua Sun:
Diffusion Imitation from Observation. - Manuel Madeira, Clément Vignac, Dorina Thanou, Pascal Frossard:
Generative Modelling of Structurally Constrained Graphs. - Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan:
Efficient Discrepancy Testing for Learning with Distribution Shift. - Thanh-Dat Truong, Utsav Prabhu, Dongyi Wang, Bhiksha Raj, Susan Gauch, Jeyamkondan Subbiah, Khoa Luu:
EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding. - Amil Dravid, Yossi Gandelsman, Kuan-Chieh Wang, Rameen Abdal, Gordon Wetzstein, Alexei A. Efros, Kfir Aberman:
Interpreting the Weight Space of Customized Diffusion Models. - Mohammadreza Salehi, Jae Sung Park, Aditya Kusupati, Ranjay Krishna, Yejin Choi, Hanna Hajishirzi, Ali Farhadi:
ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition. - Zhixian Wang, Linxiao Yang, Liang Sun, Qingsong Wen, Yi Wang:
Task-oriented Time Series Imputation Evaluation via Generalized Representers. - Robert Wu, Vardan Papyan:
Linguistic Collapse: Neural Collapse in (Large) Language Models. - Dongwon Jo, Taesu Kim, Yulhwa Kim, Jae-Joon Kim:
Mixture of Scales: Memory-Efficient Token-Adaptive Binarization for Large Language Models. - Xiaohong Chen, Canran Xiao, Yongmei Liu:
Confusion-Resistant Federated Learning via Diffusion-Based Data Harmonization on Non-IID Data. - Nived Rajaraman, Marco Bondaschi, Ashok Vardhan Makkuva, Kannan Ramchandran, Michael Gastpar:
Transformers on Markov data: Constant depth suffices. - Zhichao Hou, Weizhi Gao, Yuchen Shen, Feiyi Wang, Xiaorui Liu:
ProTransformer: Robustify Transformers via Plug-and-Play Paradigm. - Bosi Wen, Pei Ke, Xiaotao Gu, Lindong Wu, Hao Huang, Jinfeng Zhou, Wenchuang Li, Binxin Hu, Wendy Gao, Jiaxing Xu, Yiming Liu, Jie Tang, Hongning Wang, Minlie Huang:
Benchmarking Complex Instruction-Following with Multiple Constraints Composition. - Taihang Hu, Linxuan Li, Joost van de Weijer, Hongcheng Gao, Fahad Shahbaz Khan, Jian Yang, Ming-Ming Cheng, Kai Wang, Yaxing Wang:
Token Merging for Training-Free Semantic Binding in Text-to-Image Synthesis. - Bozhen Hu, Cheng Tan, Jun Xia, Yue Liu, Lirong Wu, Jiangbin Zheng, Yongjie Xu, Yufei Huang, Stan Z. Li:
Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure. - Zixiao Wang, Jicong Fan:
Graph Classification via Reference Distribution Learning: Theory and Practice. - Giangiacomo Mercatali, Yogesh Verma, André Freitas, Vikas Garg:
Diffusion Twigs with Loop Guidance for Conditional Graph Generation. - Kasra Jalaldoust, Alexis Bellot, Elias Bareinboim:
Partial Transportability for Domain Generalization. - Vladimir Kostic, Hélène Halconruy, Timothée Devergne, Karim Lounici, Massimiliano Pontil:
Learning the Infinitesimal Generator of Stochastic Diffusion Processes. - Kun Chen, Peng Ye, Hao Chen, Kang Chen, Tao Han, Wanli Ouyang, Tao Chen, Lei Bai:
FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation. - Sebastian Allmeier, Nicolas Gast:
Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise. - Xinting Huang, Madhur Panwar, Navin Goyal, Michael Hahn:
InversionView: A General-Purpose Method for Reading Information from Neural Activations. - Shantanu Jaiswal, Debaditya Roy, Basura Fernando, Cheston Tan:
Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios. - Yuchen Zhou, Emmy Liu, Graham Neubig, Michael J. Tarr, Leila Wehbe:
Divergences between Language Models and Human Brains. - Chi-Chang Lee, Zhang-Wei Hong, Pulkit Agrawal:
Going Beyond Heuristics by Imposing Policy Improvement as a Constraint. - Rohan Alur, Manish Raghavan, Devavrat Shah:
Human Expertise in Algorithmic Prediction. - Feng Xiao, Jicong Fan:
Unsupervised Anomaly Detection in The Presence of Missing Values. - Yuanbin Zou, Ziyun Huang, Jinhui Xu, Jianxin Wang, Qilong Feng:
Linear Time Approximation Algorithm for Column Subset Selection with Local Search. - Kedar Karhadkar, Michael Murray, Guido F. Montúfar:
Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension. - Peter Súkeník, Christoph H. Lampert, Marco Mondelli:
Neural collapse vs. low-rank bias: Is deep neural collapse really optimal? - Sam Olesker-Taylor, Luca Zanetti:
An Analysis of Elo Rating Systems via Markov Chains. - Yingcong Li, Ankit Singh Rawat, Samet Oymak:
Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond. - David Smerkous, Qinxun Bai, Fuxin Li:
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA. - Lennart Bürger, Fred A. Hamprecht, Boaz Nadler:
Truth is Universal: Robust Detection of Lies in LLMs. - Marta Gentiloni Silveri, Alain Durmus, Giovanni Conforti:
Theoretical guarantees in KL for Diffusion Flow Matching. - Man Zhou:
Improving the Learning Capability of Small-size Image Restoration Network by Deep Fourier Shifting. - Michael Katz, Harsha Kokel, Kavitha Srinivas, Shirin Sohrabi:
Thought of Search: Planning with Language Models Through The Lens of Efficiency. - Weichao Zeng, Yan Shu, Zhenhang Li, Dongbao Yang, Yu Zhou:
TextCtrl: Diffusion-based Scene Text Editing with Prior Guidance Control. - Xiaohe Bo, Zeyu Zhang, Quanyu Dai, Xueyang Feng, Lei Wang, Rui Li, Xu Chen, Ji-Rong Wen:
Reflective Multi-Agent Collaboration based on Large Language Models. - Dingkang Yang, Jinjie Wei, Dongling Xiao, Shunli Wang, Tong Wu, Gang Li, Mingcheng Li, Shuaibing Wang, Jiawei Chen, Yue Jiang, Qingyao Xu, Ke Li, Peng Zhai, Lihua Zhang:
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications. - Zhihan Liu, Miao Lu, Shenao Zhang, Boyi Liu, Hongyi Guo, Yingxiang Yang, Jose H. Blanchet, Zhaoran Wang:
Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer. - Lijun Zhang, Lin Li, Wei Wei, Huizhong Song, Yaodong Yang, Jiye Liang:
Scalable Constrained Policy Optimization for Safe Multi-agent Reinforcement Learning. - Xudong Wang, Jingfeng Yang, Trevor Darrell:
Segment Anything without Supervision. - Qi Pang, Shengyuan Hu, Wenting Zheng, Virginia Smith:
No Free Lunch in LLM Watermarking: Trade-offs in Watermarking Design Choices. - Heiko Zimmermann, Christian Andersson Naesseth, Jan-Willem van de Meent:
VISA: Variational Inference with Sequential Sample-Average Approximations. - Tianbo Li, Zekun Shi, Jiaxi Zhao, Min Lin:
Amortized Eigendecomposition for Neural Networks. - Xixi Hu, Qiang Liu, Xingchao Liu, Bo Liu:
AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies. - Matthew Bendel, Rizwan Ahmad, Philip Schniter:
pcaGAN: Improving Posterior-Sampling cGANs via Principal Component Regularization. - Sirine Ayadi, Leon Hetzel, Johanna Sommer, Fabian J. Theis, Stephan Günnemann:
Unified Guidance for Geometry-Conditioned Molecular Generation. - Ge Gao, Xi Yang, Qitong Gao, Song Ju, Miroslav Pajic, Min Chi:
Off-Policy Selection for Initiating Human-Centric Experimental Design. - Lingyu Zhang, Zhengran Ji, Nicholas R. Waytowich, Boyuan Chen:
GUIDE: Real-Time Human-Shaped Agents. - Chaoyang Wang, Xiangtai Li, Lu Qi, Henghui Ding, Yunhai Tong, Ming-Hsuan Yang:
SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified Flow. - Qingwen Bu, Jia Zeng, Li Chen, Yanchao Yang, Guyue Zhou, Junchi Yan, Ping Luo, Heming Cui, Yi Ma, Hongyang Li:
Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation. - Eric Qu, Aditi S. Krishnapriyan:
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains. - Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ilkan Ceylan, Michael M. Bronstein, Avishek Joey Bose:
Fisher Flow Matching for Generative Modeling over Discrete Data. - Zeren Xiong, Zedong Zhang, Zikun Chen, Shuo Chen, Xiang Li, Gan Sun, Jian Yang, Jun Li:
Novel Object Synthesis via Adaptive Text-Image Harmony. - Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson:
Evaluating Copyright Takedown Methods for Language Models. - Yao Lai, Jinxin Liu, David Z. Pan, Ping Luo:
Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier Designs. - Daniel Tan, David Chanin, Aengus Lynch, Brooks Paige, Dimitrios Kanoulas, Adrià Garriga-Alonso, Robert Kirk:
Analysing the Generalisation and Reliability of Steering Vectors. - Austin Watkins, Thanh Nguyen-Tang, Enayat Ullah, Raman Arora:
Adversarially Robust Multi-task Representation Learning. - Yuze He, Wang Zhao, Shaohui Liu, Yubin Hu, Yushi Bai, Yu-Hui Wen, Yongjin Liu:
AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos. - Yuan Deng, Jieming Mao, Vahab Mirrokni, Hanrui Zhang, Song Zuo:
Efficiency of the First-Price Auction in the Autobidding World. - Xuan Shen, Pu Zhao, Yifan Gong, Zhenglun Kong, Zheng Zhan, Yushu Wu, Ming Lin, Chao Wu, Xue Lin, Yanzhi Wang:
Search for Efficient Large Language Models. - Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen:
Query-Efficient Correlation Clustering with Noisy Oracle. - Yushi Hu, Weijia Shi, Xingyu Fu, Dan Roth, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Ranjay Krishna:
Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models. - Nathan Stromberg, Rohan Ayyagari, Sanmi Koyejo, Richard Nock, Lalitha Sankar:
Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections. - Nicolas Zucchet, Antonio Orvieto:
Recurrent neural networks: vanishing and exploding gradients are not the end of the story. - Xun Wu, Shaohan Huang, Guolong Wang, Jing Xiong, Furu Wei:
Boosting Text-to-Video Generative Model with MLLMs Feedback. - Bethia Sun, Maurice Pagnucco, Yang Song:
Fully Distributed, Flexible Compositional Visual Representations via Soft Tensor Products. - Nitzan Bitton Guetta, Aviv Slobodkin, Aviya Maimon, Eliya Habba, Royi Rassin, Yonatan Bitton, Idan Szpektor, Amir Globerson, Yuval Elovici:
Visual Riddles: a Commonsense and World Knowledge Challenge for Large Vision and Language Models. - Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra:
Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior. - Diyuan Wu, Ionut-Vlad Modoranu, Mher Safaryan, Denis Kuznedelev, Dan Alistarh:
The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information. - Juan Formanek, Callum Rhys Tilbury, Louise Beyers, Jonathan P. Shock, Arnu Pretorius:
Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation. - Alexandros Haliassos, Rodrigo Mira, Honglie Chen, Zoe Landgraf, Stavros Petridis, Maja Pantic:
Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs. - Guotao Liang, Baoquan Zhang, Yaowei Wang, Yunming Ye, Xutao Li, Huaibin Wang, Chuyao Luo, Kola Ye, Linfeng Luo:
LG-VQ: Language-Guided Codebook Learning. - Hanlin Chen, Fangyin Wei, Chen Li, Tianxin Huang, Yunsong Wang, Gim Hee Lee:
VCR-GauS: View Consistent Depth-Normal Regularizer for Gaussian Surface Reconstruction. - Jiaqi Tang, Hao Lu, Ruizheng Wu, Xiaogang Xu, Ke Ma, Cheng Fang, Bin Guo, Jiangbo Lu, Qifeng Chen, Yingcong Chen:
HAWK: Learning to Understand Open-World Video Anomalies. - Akiyoshi Tomihari, Issei Sato:
Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective. - Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Nearly Optimal Approximation of Matrix Functions by the Lanczos Method. - Linhui Xiao, Xiaoshan Yang, Fang Peng, Yaowei Wang, Changsheng Xu:
OneRef: Unified One-tower Expression Grounding and Segmentation with Mask Referring Modeling. - Tianchi Liao, Lele Fu, Jialong Chen, Zhen Wang, Zibin Zheng, Chuan Chen:
A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm. - Lei Ding, Yang Hu, Nicole Denier, Enze Shi, Junxi Zhang, Qirui Hu, Karen D. Hughes, Linglong Kong, Bei Jiang:
Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach. - Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri:
Safety through feedback in Constrained RL. - Xudong Yu, Chenjia Bai, Haoran He, Changhong Wang, Xuelong Li:
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment. - Akide Liu, Jing Liu, Zizheng Pan, Yefei He, Reza Haffari, Bohan Zhuang:
MiniCache: KV Cache Compression in Depth Dimension for Large Language Models. - István Sárándi, Gerard Pons-Moll:
Neural Localizer Fields for Continuous 3D Human Pose and Shape Estimation. - Simon Buchholz:
Learning Partitions from Context. - Olaf Lipinski, Adam J. Sobey, Federico Cerutti, Timothy J. Norman:
Speaking Your Language: Spatial Relationships in Interpretable Emergent Communication. - Zhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu, Dejia Xu, Zhangyang Wang:
LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS. - Yaran Fan, Jamie Pool, Senja Filipi, Ross Cutler:
Topic-Conversation Relevance (TCR) Dataset and Benchmarks. - Kai Wu, Yujian Betterest Li, Jian Lou, Xiaoyu Zhang, Handing Wang, Jing Liu:
Rapid Plug-in Defenders. - Julia Gastinger, Shenyang Huang, Michael Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau:
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs. - Lingkai Kong, Molei Tao:
Quantitative Convergences of Lie Group Momentum Optimizers. - Tao Ma, Hongbin Zhou, Qiusheng Huang, Xuemeng Yang, Jianfei Guo, Bo Zhang, Min Dou, Yu Qiao, Botian Shi, Hongsheng Li:
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving. - Qian Lin, Zongkai Liu, Danying Mo, Chao Yu:
An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning. - John Arevalo, Ellen Su, Anne E. Carpenter, Shantanu Singh:
MOTIVE: A Drug-Target Interaction Graph For Inductive Link Prediction. - Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Y. Zou, Huaxiu Yao:
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. - Yang Cai, Constantinos Daskalakis, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
On Tractable Φ-Equilibria in Non-Concave Games. - Muhammad Faaiz Taufiq, Jean-Francois Ton, Yang Liu:
Achievable Fairness on Your Data With Utility Guarantees. - Julia B. Nakhleh, Joseph Shenouda, Robert D. Nowak:
A New Neural Kernel Regime: The Inductive Bias of Multi-Task Learning. - Miguel González Duque, Richard Michael, Simon Bartels, Yevgen Zainchkovskyy, Søren Hauberg, Wouter Boomsma:
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences. - Lingbing Guo, Zhongpu Bo, Zhuo Chen, Yichi Zhang, Jiaoyan Chen, Yarong Lan, Mengshu Sun, Zhiqiang Zhang, Yangyifei Luo, Qian Li, Qiang Zhang, Wen Zhang, Huajun Chen:
MKGL: Mastery of a Three-Word Language. - Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S. Dhillon, Yulia Tsvetkov, Hanna Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain:
MatFormer: Nested Transformer for Elastic Inference. - Ke Xue, Ruo-Tong Chen, Xi Lin, Yunqi Shi, Shixiong Kai, Siyuan Xu, Chao Qian:
Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer. - Shanghua Gao, Teddy Koker, Owen Queen, Tom Hartvigsen, Theodoros Tsiligkaridis, Marinka Zitnik:
UniTS: A Unified Multi-Task Time Series Model. - Tony Lee, Haoqin Tu, Chi Heem Wong, Wenhao Zheng, Yiyang Zhou, Yifan Mai, Josselin Somerville Roberts, Michihiro Yasunaga, Huaxiu Yao, Cihang Xie, Percy Liang:
VHELM: A Holistic Evaluation of Vision Language Models. - Johannes Treutlein, Dami Choi, Jan Betley, Samuel Marks, Cem Anil, Roger B. Grosse, Owain Evans:
Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data. - Pengyu Chen, Xu Shi, Rujun Jiang, Jiulin Wang:
Penalty-based Methods for Simple Bilevel Optimization under Hölderian Error Bounds. - Jie Yang, Wang Zeng, Sheng Jin, Lumin Xu, Wentao Liu, Chen Qian, Ruimao Zhang:
KptLLM: Unveiling the Power of Large Language Model for Keypoint Comprehension. - Anand Gopalakrishnan, Aleksandar Stanic, Jürgen Schmidhuber, Michael C. Mozer:
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery. - Tankala Pavan Kalyan, Piyush Singh Pasi, Sahil Dharod, Azeem Motiwala, Preethi Jyothi, Aditi Chaudhary, Krishna Srinivasan:
WikiDO: A New Benchmark Evaluating Cross-Modal Retrieval for Vision-Language Models. - Emanuele Vivoli, Marco Bertini, Dimosthenis Karatzas:
CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding. - Amelia Johnson, Michael A. Buice, Koosha Khalvati:
A Unifying Normative Framework of Decision Confidence. - Richard Nock, Ehsan Amid, Frank Nielsen, Alexander Soen, Manfred K. Warmuth:
Hyperbolic Embeddings of Supervised Models. - Xiongkun Linghu, Jiangyong Huang, Xuesong Niu, Xiaojian (Shawn) Ma, Baoxiong Jia, Siyuan Huang:
Multi-modal Situated Reasoning in 3D Scenes. - Yassine Laguel, Yasa Syed, Necdet Serhat Aybat, Mert Gürbüzbalaban:
High-probability complexity bounds for stochastic non-convex minimax optimization. - David Durfee:
Instance-Specific Asymmetric Sensitivity in Differential Privacy. - Xin Yang, Wending Yan, Michael Bi Mi, Yuan Yuan, Robby T. Tan:
End-to-End Video Semantic Segmentation in Adverse Weather using Fusion Blocks and Temporal-Spatial Teacher-Student Learning. - Mingfei Chen, Eli Shlizerman:
AV-Cloud: Spatial Audio Rendering Through Audio-Visual Cloud Splatting. - Xin Li, Weize Chen, Qizhi Chu, Haopeng Li, Zhaojun Sun, Ran Li, Chen Qian, Yiwei Wei, Chuan Shi, Zhiyuan Liu, Maosong Sun, Cheng Yang:
Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models. - Saeed Masoudian, Julian Zimmert, Yevgeny Seldin:
A Best-of-both-worlds Algorithm for Bandits with Delayed Feedback with Robustness to Excessive Delays. - Johnny Xi, Jana Osea, Zuheng Xu, Jason S. Hartford:
Propensity Score Alignment of Unpaired Multimodal Data. - Haian Jin, Yuan Li, Fujun Luan, Yuanbo Xiangli, Sai Bi, Kai Zhang, Zexiang Xu, Jin Sun, Noah Snavely:
Neural Gaffer: Relighting Any Object via Diffusion. - Xiaodong Lu, Leilei Sun, Tongyu Zhu, Weifeng Lv:
Improving Temporal Link Prediction via Temporal Walk Matrix Projection. - Wanru Zhao, Hongxiang Fan, Shell Xu Hu, Wangchunshu Zhou, Nicholas D. Lane:
CLUES: Collaborative Private-domain High-quality Data Selection for LLMs via Training Dynamics. - Siddhant Haldar, Zhuoran Peng, Lerrel Pinto:
BAKU: An Efficient Transformer for Multi-Task Policy Learning. - Talfan Evans, Nikhil Parthasarathy, Hamza Merzic, Olivier J. Hénaff:
Data curation via joint example selection further accelerates multimodal learning. - Timing Yang, Yuanliang Ju, Li Yi:
ImOV3D: Learning Open Vocabulary Point Clouds 3D Object Detection from Only 2D Images. - Lujun Li, Peijie Dong, Zhenheng Tang, Xiang Liu, Qiang Wang, Wenhan Luo, Wei Xue, Qifeng Liu, Xiaowen Chu, Yike Guo:
Discovering Sparsity Allocation for Layer-wise Pruning of Large Language Models. - Benjie Wang, Denis Deratani Mauá, Guy Van den Broeck, YooJung Choi:
A Compositional Atlas for Algebraic Circuits. - Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel R. Sheldon:
Efficient and Private Marginal Reconstruction with Local Non-Negativity. - Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier:
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. - Guy Kornowski, Swati Padmanabhan, Kai Wang, Zhe Zhang, Suvrit Sra:
First-Order Methods for Linearly Constrained Bilevel Optimization. - Chenggang Chen, Zhiyu Yang, Xiaoqin Wang:
Neural Embeddings Rank: Aligning 3D latent dynamics with movements. - Maryam Aliakbarpour, Mark Bun, Adam Smith:
Optimal Hypothesis Selection in (Almost) Linear Time. - Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh, Xingzhi Guo, Deqing Yang, Yanghua Xiao:
Iterative Methods via Locally Evolving Set Process.
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