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ORCIDJiang Bian 0002
Person information
- affiliation: Microsoft Research Asia, Beijing, China
- affiliation (former): Yahoo! Labs, Sunnyvale, CA, USA
- affiliation (PhD 2010): Georgia Institute of Technology, Atlanta, GA, USA
Other persons with the same name
- Jiang Bian — disambiguation page
- Jiang Bian 0001
![[0000-0002-2238-5429]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-2238-5429")
— University of Florida, Department of Health Outcomes and Biomedical Informatics, Gainesville, FL, USA (and 1 more) - Jiang Bian 0003 — Baidu Research, Big Data Laboratory, Beijing, China (and 1 more)
- Jiang Bian 0004 — Chinese Academy of Sciences, Institute of Automation, State Key Laboratory for Management and Control of Complex Systems, Beijing, China
- Jiang Bian 0005 — Northwest A&F University, Yangling, China
- Jiang Bian 0006 — University of Technology Sydney, Australia
- Jiang Bian 0007 — University of Hong Kong, Pokfulam, Hong Kong
- Jiang Bian 0008 — Shanghai Jiaotong University, Department of Computer Science and Engineering, China
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2020 – today
- 2025
[c113]Yuchi Wang, Junliang Guo, Jianhong Bai, Runyi Yu, Tianyu He, Xu Tan, Xu Sun, Jiang Bian:
InstructAvatar: Text-Guided Emotion and Motion Control for Avatar Generation. AAAI 2025: 8132-8140- [c112]Yu-Hao Huang, Chang Xu, Yueying Wu, Wu-Jun Li, Jiang Bian:
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts. AAAI 2025: 17520-17527 - [c111]Wei Fan, Shun Zheng, Pengyang Wang, Rui Xie, Kun Yi, Qi Zhang, Jiang Bian, Yanjie Fu:
IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting. KDD (1) 2025: 295-306 - [c110]Min Hou, Yueying Wu, Chang Xu, Yu-Hao Huang, Chenxi Bai, Le Wu, Jiang Bian:
InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models. KDD (1) 2025: 472-483 - [i130]Hanxin Zhu, Tianyu He, Xiqian Yu, Junliang Guo, Zhibo Chen, Jiang Bian:
AR4D: Autoregressive 4D Generation from Monocular Videos. CoRR abs/2501.01722 (2025) - [i129]Yu-Hao Huang, Chang Xu, Yueying Wu, Wu-Jun Li, Jiang Bian:
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts. CoRR abs/2501.05403 (2025) - [i128]Xumeng Wen, Shun Zheng, Zhen Xu, Yiming Sun, Jiang Bian:
Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models. CoRR abs/2502.03147 (2025) - [i127]Yu Yuan, Shizhao Sun, Qi Liu, Jiang Bian:
CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD Editing. CoRR abs/2502.03997 (2025) - [i126]Panqi Chen, Lei Cheng, Jianlong Li, Weichang Li, Weiqing Liu, Jiang Bian, Shikai Fang:
Generalized Temporal Tensor Decomposition with Rank-revealing Latent-ODE. CoRR abs/2502.06164 (2025) - [i125]Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Ren-He Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian:
BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modelling. CoRR abs/2503.02445 (2025) - [i124]Yang Ye, Junliang Guo, Haoyu Wu, Tianyu He, Tim Pearce, Tabish Rashid, Katja Hofmann, Jiang Bian:
Fast Autoregressive Video Generation with Diagonal Decoding. CoRR abs/2503.14070 (2025) - [i123]Zijian Li, Jingjing Fu, Lei Song, Jiang Bian, Jun Zhang, Rui Wang:
Chain of Functions: A Programmatic Pipeline for Fine-Grained Chart Reasoning Data. CoRR abs/2503.16260 (2025) - 2024
- [j18]Xinquan Huang, Wenlei Shi, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu:
LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data. Neural Networks 176: 106354 (2024) - [j17]Anni Tang, Tianyu He, Xu Tan, Jun Ling, Runnan Li, Sheng Zhao, Jiang Bian, Li Song:
Memories are One-to-Many Mapping Alleviators in Talking Face Generation. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 8758-8770 (2024) - [j16]Velma K. Lopez, Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O'Dea, Madeline Adee, Turgay Ayer, Jagpreet Chhatwal, Ozden O. Dalgic, Mary A. Ladd, Benjamin P. Linas, Peter P. Mueller, Jade Xiao, Johannes Bracher, Alvaro J. Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Yuxin Huang, Dasuni Jayawardena, Abdul H. Kanji, Khoa Le, Anja Mühlemann, Jarad Niemi, Evan L. Ray, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W. Zorn, Sen Pei, Jeffrey Shaman, Teresa K. Yamana, Samuel R. Tarasewicz, Daniel J. Wilson, Sid Baccam, Heidi Gurung, Steve Stage, Brad Suchoski, Lei Gao, Zhiling Gu, Myungjin Kim, Xinyi Li, Guannan Wang, Lily Wang, Yueying Wang, Shan Yu, Lauren Gardner, Sonia Jindal, Maximilian Marshall, Kristen Nixon, Juan Dent, Alison L. Hill, Joshua Kaminsky, Elizabeth C. Lee, Joseph Chadi Lemaitre, Justin Lessler, Claire P. Smith, Shaun Truelove, Matt Kinsey, Luke C. Mullany, Kaitlin Rainwater-Lovett, Lauren Shin, Katharine Tallaksen, Shelby Wilson, Dean Karlen, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Jiang Bian, Wei Cao, Zhifeng Gao, Juan Lavista Ferres, Chaozhuo Li, Tie-Yan Liu, Xing Xie, Shun Zhang, Shun Zheng, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana L. Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Robert Walraven, Jinghui Chen, Quanquan Gu, Lingxiao Wang, Pan Xu, Weitong Zhang, Difan Zou, Graham Casey Gibson, Daniel Sheldon, Ajitesh Srivastava, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Lijing Wang, Pragati V. Prasad, Jo W. Walker, Alexander E. Webber, Rachel B. Slayton, Matthew Biggerstaff, Nicholas G. Reich, Michael A. Johansson:
Challenges of COVID-19 Case Forecasting in the US, 2020-2021. PLoS Comput. Biol. 20(5): 1011200 (2024) - [j15]Wei Fan, Yanjie Fu, Shun Zheng, Jiang Bian, Yuanchun Zhou, Hui Xiong:
DEWP: Deep Expansion Learning for Wind Power Forecasting. ACM Trans. Knowl. Discov. Data 18(3): 71:1-71:21 (2024) - [j14]Yang Liu, Chang Xu, Min Hou, Weiqing Liu, Jiang Bian, Qi Liu, Tie-Yan Liu:
Digger-Guider: High-Frequency Factor Extraction for Stock Trend Prediction. IEEE Trans. Knowl. Data Eng. 36(12): 7973-7985 (2024) - [j13]Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu:
NuTime: Numerically Multi-Scaled Embedding for Large- Scale Time-Series Pretraining. Trans. Mach. Learn. Res. 2024 (2024) - [j12]Linjie Xu, Zhengyao Jiang, Jinyu Wang, Lei Song, Jiang Bian:
Mildly Constrained Evaluation Policy for Offline Reinforcement Learning. Trans. Mach. Learn. Res. 2024 (2024) - [c109]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. AAAI 2024: 22614-22622 - [c108]Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim:
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. ACL (1) 2024: 8252-8271 - [c107]Qingyan Guo, Rui Wang, Junliang Guo, Xu Tan, Jiang Bian, Yujiu Yang:
Mitigating Reversal Curse in Large Language Models via Semantic-aware Permutation Training. ACL (Findings) 2024: 11453-11464 - [c106]Linjie Xu, Zichuan Liu, Alexander Dockhorn, Diego Perez Liebana, Jinyu Wang, Lei Song, Jiang Bian:
Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning. CoG 2024: 1-8 - [c105]Henan Wang, Hanxin Zhu, Tianyu He, Runsen Feng, Jiajun Deng, Jiang Bian, Zhibo Chen:
End-to-End Rate-Distortion Optimized 3D Gaussian Representation. ECCV (58) 2024: 76-92 - [c104]Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian:
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process. ICLR 2024 - [c103]Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang:
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers. ICLR 2024 - [c102]Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, Han Hu, HsiangTao Wu, Sheng Zhao, Jiang Bian:
GAIA: Zero-shot Talking Avatar Generation. ICLR 2024 - [c101]Yichong Leng, Zhifang Guo, Kai Shen, Zeqian Ju, Xu Tan, Eric Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiangyang Li, Sheng Zhao, Tao Qin, Jiang Bian:
PromptTTS 2: Describing and Generating Voices with Text Prompt. ICLR 2024 - [c100]Kai Shen, Zeqian Ju, Xu Tan, Eric Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian:
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers. ICLR 2024 - [c99]Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian:
BatteryML: An Open-source Platform for Machine Learning on Battery Degradation. ICLR 2024 - [c98]Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian:
Whittle Index with Multiple Actions and State Constraint for Inventory Management. ICLR 2024 - [c97]Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin, Dongchao Yang, Eric Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiangyang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao:
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models. ICML 2024 - [c96]Yifan Xia, Xianliang Yang, Zichuan Liu, Zhihao Liu, Lei Song, Jiang Bian:
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems. ICML 2024 - [c95]Dongchao Yang, Jinchuan Tian, Xu Tan, Rongjie Huang, Songxiang Liu, Haohan Guo, Xuankai Chang, Jiatong Shi, Sheng Zhao, Jiang Bian, Zhou Zhao, Xixin Wu, Helen M. Meng:
UniAudio: Towards Universal Audio Generation with Large Language Models. ICML 2024 - [c94]Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim:
Diversification of Adaptive Policy for Effective Offline Reinforcement Learning. IJCAI 2024: 3863-3871 - [c93]Xumeng Wen, Han Zhang, Shun Zheng, Wei Xu, Jiang Bian:
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models. KDD 2024: 3323-3333 - [c92]Zhujin Gao, Junliang Guo, Xu Tan, Yongxin Zhu, Fang Zhang, Jiang Bian, Linli Xu:
Empowering Diffusion Models on the Embedding Space for Text Generation. NAACL-HLT 2024: 4664-4683 - [c91]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. NeurIPS 2024 - [c90]Jiawen Zhang, Xumeng Wen, Zhenwei Zhang, Shun Zheng, Jia Li, Jiang Bian:
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons. NeurIPS 2024 - [c89]Jiawen Zhang, Shun Zheng, Xumeng Wen, Xiaofang Zhou, Jiang Bian, Jia Li:
ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer. NeurIPS 2024 - [c88]Hanxin Zhu, Tianyu He, Anni Tang, Junliang Guo, Zhibo Chen, Jiang Bian:
Compositional 3D-aware Video Generation with LLM Director. NeurIPS 2024 - [i122]Wei Fan, Yanjie Fu, Shun Zheng, Jiang Bian, Yuanchun Zhou, Hui Xiong:
DEWP: Deep Expansion Learning for Wind Power Forecasting. CoRR abs/2401.00644 (2024) - [i121]Wei Fan, Shun Zheng, Pengyang Wang, Rui Xie, Jiang Bian, Yanjie Fu:
Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows. CoRR abs/2401.16777 (2024) - [i120]Jianhong Bai, Tianyu He, Yuchi Wang, Junliang Guo, Haoji Hu, Zuozhu Liu, Jiang Bian:
UniEdit: A Unified Tuning-Free Framework for Video Motion and Appearance Editing. CoRR abs/2402.13185 (2024) - [i119]Qingyan Guo, Rui Wang, Junliang Guo, Xu Tan, Jiang Bian, Yujiu Yang:
Mitigating Reversal Curse in Large Language Models via Semantic-aware Permutation Training. CoRR abs/2403.00758 (2024) - [i118]Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin, Dongchao Yang, Yanqing Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiang-Yang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao:
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models. CoRR abs/2403.03100 (2024) - [i117]Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian:
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process. CoRR abs/2403.05751 (2024) - [i116]Linjie Xu, Zichuan Liu, Alexander Dockhorn, Diego Perez Liebana, Jinyu Wang, Lei Song, Jiang Bian:
Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning. CoRR abs/2404.09715 (2024) - [i115]Guangran Cheng, Chuheng Zhang, Wenzhe Cai, Li Zhao, Changyin Sun, Jiang Bian:
Empowering Large Language Models on Robotic Manipulation with Affordance Prompting. CoRR abs/2404.11027 (2024) - [i114]Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian:
RD2Bench: Toward Data-Centric Automatic R&D. CoRR abs/2404.11276 (2024) - [i113]Chao Zhou, Huishuai Zhang, Jiang Bian, Weiming Zhang, Nenghai Yu:
\copyright Plug-in Authorization for Human Content Copyright Protection in Text-to-Image Model. CoRR abs/2404.11962 (2024) - [i112]Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian:
Protecting Your LLMs with Information Bottleneck. CoRR abs/2404.13968 (2024) - [i111]Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang:
DPO Meets PPO: Reinforced Token Optimization for RLHF. CoRR abs/2404.18922 (2024) - [i110]Yuchi Wang, Junliang Guo, Jianhong Bai, Runyi Yu, Tianyu He, Xu Tan, Xu Sun, Jiang Bian:
InstructAvatar: Text-Guided Emotion and Motion Control for Avatar Generation. CoRR abs/2405.15758 (2024) - [i109]Zhihao Liu, Xianliang Yang, Zichuan Liu, Yifan Xia, Wei Jiang, Yuanyu Zhang, Lijuan Li, Guoliang Fan, Lei Song, Jiang Bian:
Knowing What Not to Do: Leverage Language Model Insights for Action Space Pruning in Multi-agent Reinforcement Learning. CoRR abs/2405.16854 (2024) - [i108]Henan Wang, Hanxin Zhu, Tianyu He, Runsen Feng, Jiajun Deng, Jiang Bian, Zhibo Chen:
End-to-End Rate-Distortion Optimized 3D Gaussian Representation. CoRR abs/2406.01597 (2024) - [i107]Yifan Xia, Xianliang Yang, Zichuan Liu, Zhihao Liu, Lei Song, Jiang Bian:
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems. CoRR abs/2406.03503 (2024) - [i106]Zijian Li, Qingyan Guo, Jiawei Shao, Lei Song, Jiang Bian, Jun Zhang, Rui Wang:
Graph Neural Network Enhanced Retrieval for Question Answering of LLMs. CoRR abs/2406.06572 (2024) - [i105]Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio:
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation. CoRR abs/2406.07529 (2024) - [i104]Runyi Yu, Tianyu He, Ailing Zhang, Yuchi Wang, Junliang Guo, Xu Tan, Chang Liu, Jie Chen, Jiang Bian:
Make Your Actor Talk: Generalizable and High-Fidelity Lip Sync with Motion and Appearance Disentanglement. CoRR abs/2406.08096 (2024) - [i103]Yujiang Wu, Hongjian Song, Jiawen Zhang, Xumeng Wen, Shun Zheng, Jiang Bian:
Large Language Model as a Universal Clinical Multi-task Decoder. CoRR abs/2406.12738 (2024) - [i102]Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian:
Video In-context Learning. CoRR abs/2407.07356 (2024) - [i101]Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim:
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. CoRR abs/2407.14733 (2024) - [i100]Xu Yang, Haotian Chen, Wenjun Feng, Haoxue Wang, Zeqi Ye, Xinjie Shen, Xiao Yang, Shizhao Sun, Weiqing Liu, Jiang Bian:
Collaborative Evolving Strategy for Automatic Data-Centric Development. CoRR abs/2407.18690 (2024) - [i99]Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian:
Controllable Financial Market Generation with Diffusion Guided Meta Agent. CoRR abs/2408.12991 (2024) - [i98]Hanxin Zhu, Tianyu He, Anni Tang, Junliang Guo, Zhibo Chen, Jiang Bian:
Compositional 3D-aware Video Generation with LLM Director. CoRR abs/2409.00558 (2024) - [i97]Wenhao Zhao, Qiushui Xu, Linjie Xu, Lei Song, Jinyu Wang, Chunlai Zhou, Jiang Bian:
Enhancing Cross-domain Pre-Trained Decision Transformers with Adaptive Attention. CoRR abs/2409.06985 (2024) - [i96]Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian:
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model. CoRR abs/2409.07486 (2024) - [i95]Ruohong Liu, Yuxin Pan, Linjie Xu, Lei Song, Pengcheng You, Yize Chen, Jiang Bian:
C-MORL: Multi-Objective Reinforcement Learning through Efficient Discovery of Pareto Front. CoRR abs/2410.02236 (2024) - [i94]Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Yang, Li Zhao, Jiang Bian:
IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI. CoRR abs/2411.00785 (2024) - [i93]Jiawen Zhang, Shun Zheng, Xumeng Wen, Xiaofang Zhou, Jiang Bian, Jia Li:
ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer. CoRR abs/2411.01842 (2024) - [i92]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. CoRR abs/2411.19285 (2024) - [i91]Min Hou, Yueying Wu, Chang Xu, Yu-Hao Huang, Chenxi Bai, Le Wu, Jiang Bian:
InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models. CoRR abs/2412.08480 (2024) - [i90]Anni Tang, Tianyu He, Junliang Guo, Xinle Cheng, Li Song, Jiang Bian:
VidTok: A Versatile and Open-Source Video Tokenizer. CoRR abs/2412.13061 (2024) - [i89]Yuchi Wang, Junliang Guo, Xinyi Xie, Tianyu He, Xu Sun, Jiang Bian:
VidTwin: Video VAE with Decoupled Structure and Dynamics. CoRR abs/2412.17726 (2024) - [i88]Jiawei Lin, Shizhao Sun, Danqing Huang, Ting Liu, Ji Li, Jiang Bian:
From Elements to Design: A Layered Approach for Automatic Graphic Design Composition. CoRR abs/2412.19712 (2024) - [i87]Haoyi Zhang, Shizhao Sun, Yibo Lin, Runsheng Wang, Jiang Bian:
AnalogXpert: Automating Analog Topology Synthesis by Incorporating Circuit Design Expertise into Large Language Models. CoRR abs/2412.19824 (2024) - [i86]Huanyu Zhang, Chang Xu, Yifan Zhang, Zhang Zhang, Liang Wang, Jiang Bian, Tieniu Tan:
TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting. CoRR abs/2412.20810 (2024) - 2023
- [c87]Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian:
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. AAAI 2023: 8132-8140 - [c86]Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, Jiang Bian:
H-TSP: Hierarchically Solving the Large-Scale Traveling Salesman Problem. AAAI 2023: 9345-9353 - [c85]Yihan Wu, Junliang Guo, Xu Tan, Chen Zhang, Bohan Li, Ruihua Song, Lei He, Sheng Zhao, Arul Menezes, Jiang Bian:
VideoDubber: Machine Translation with Speech-Aware Length Control for Video Dubbing. AAAI 2023: 13772-13779 - [c84]Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. AISTATS 2023: 3034-3047 - [c83]Yuanying Cai, Chuheng Zhang, Hanye Zhao, Li Zhao, Jiang Bian:
Curriculum Offline Reinforcement Learning. AAMAS 2023: 1221-1229 - [c82]Dingyao Yu, Kaitao Song, Peiling Lu, Tianyu He, Xu Tan, Wei Ye, Shikun Zhang, Jiang Bian:
MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models. EMNLP (Demos) 2023: 246-255 - [c81]Zenghao Chai, Tianke Zhang, Tianyu He, Xu Tan, Tadas Baltrusaitis, HsiangTao Wu, Runnan Li, Sheng Zhao, Chun Yuan, Jiang Bian:
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details. ICCV 2023: 9053-9064 - [c80]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. ICDE 2023: 2593-2606 - [c79]Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian:
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. ICLR 2023 - [c78]Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian:
Robust Situational Reinforcement Learning in Face of Context Disturbances. ICML 2023: 41973-41989 - [c77]Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, Tie-Yan Liu:
Web-based Long-term Spine Treatment Outcome Forecasting. KDD 2023: 3082-3092 - [c76]Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li:
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. KDD 2023: 3273-3285 - [c75]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. KDD 2023: 4003-4012 - [c74]Lewen Wang, Haozhe Zhao, Cunguang Feng, Weiqing Liu, Congrui Huang, Marco Santoni, Manuel Cristofaro, Paola Jafrancesco, Jiang Bian:
Removing Camouflage and Revealing Collusion: Leveraging Gang-crime Pattern in Fraudster Detection. KDD 2023: 5104-5115 - [c73]Chenpeng Du, Qi Chen, Tianyu He, Xu Tan, Xie Chen, Kai Yu, Sheng Zhao, Jiang Bian:
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder. ACM Multimedia 2023: 4281-4289 - [c72]Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley Llorens:
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning. NeurIPS 2023 - [c71]Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian:
On the Generalization Properties of Diffusion Models. NeurIPS 2023 - [c70]Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao:
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models. NeurIPS 2023 - [i85]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. CoRR abs/2301.08846 (2023) - [i84]Kai Shen, Junliang Guo, Xu Tan, Siliang Tang, Rui Wang, Jiang Bian:
A Study on ReLU and Softmax in Transformer. CoRR abs/2302.06461 (2023) - [i83]Zenghao Chai, Tianke Zhang, Tianyu He, Xu Tan, Tadas Baltrusaitis, HsiangTao Wu, Runnan Li, Sheng Zhao, Chun Yuan, Jiang Bian:
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details. CoRR abs/2303.11225 (2023) - [i82]Chenpeng Du, Qi Chen, Tianyu He, Xu Tan, Xie Chen, Kai Yu, Sheng Zhao, Jiang Bian:
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder. CoRR abs/2303.17550 (2023) - [i81]Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao:
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models. CoRR abs/2304.00830 (2023) - [i80]Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian:
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers. CoRR abs/2304.09116 (2023) - [i79]Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, Jiang Bian:
H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem. CoRR abs/2304.09395 (2023) - [i78]Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian:
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. CoRR abs/2304.09407 (2023) - [i77]Shufang Xie, Huishuai Zhang, Junliang Guo, Xu Tan, Jiang Bian, Hany Hassan Awadalla, Arul Menezes, Tao Qin, Rui Yan:
ResiDual: Transformer with Dual Residual Connections. CoRR abs/2304.14802 (2023) - [i76]Ang Lv, Xu Tan, Peiling Lu, Wei Ye, Shikun Zhang, Jiang Bian, Rui Yan:
GETMusic: Generating Any Music Tracks with a Unified Representation and Diffusion Framework. CoRR abs/2305.10841 (2023) - [i75]Bei Li, Rui Wang, Junliang Guo, Kaitao Song, Xu Tan, Hany Hassan, Arul Menezes, Tong Xiao, Jiang Bian, JingBo Zhu:
Deliberate then Generate: Enhanced Prompting Framework for Text Generation. CoRR abs/2305.19835 (2023) - [i74]Peiling Lu, Xin Xu, Chenfei Kang, Botao Yu, Chengyi Xing, Xu Tan, Jiang Bian:
MuseCoco: Generating Symbolic Music from Text. CoRR abs/2306.00110 (2023) - [i73]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. CoRR abs/2306.01997 (2023) - [i72]Linjie Xu, Zhengyao Jiang, Jinyu Wang, Lei Song, Jiang Bian:
Mildly Constrained Evaluation Policy for Offline Reinforcement Learning. CoRR abs/2306.03680 (2023) - [i71]Xianliang Yang, Zhihao Liu, Wei Jiang, Chuheng Zhang, Li Zhao, Lei Song, Jiang Bian:
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management. CoRR abs/2306.07542 (2023) - [i70]Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li:
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. CoRR abs/2306.09368 (2023) - [i69]Chenfei Kang, Peiling Lu, Botao Yu, Xu Tan, Wei Ye, Shikun Zhang, Jiang Bian:
EmoGen: Eliminating Subjective Bias in Emotional Music Generation. CoRR abs/2307.01229 (2023) - [i68]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. CoRR abs/2307.03119 (2023) - [i67]Tianlang He, Keyan Lu, Chang Xu, Yang Liu, Weiqing Liu, S.-H. Gary Chan, Jiang Bian:
Efficient Behavior-consistent Calibration for Multi-agent Market Simulation. CoRR abs/2307.12987 (2023) - [i66]Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian:
Pre-Trained Large Language Models for Industrial Control. CoRR abs/2308.03028 (2023) - [i65]Xianfeng Jiao, Zizhong Li, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian:
Microstructure-Empowered Stock Factor Extraction and Utilization. CoRR abs/2308.08135 (2023) - [i64]Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian:
PromptTTS 2: Describing and Generating Voices with Text Prompt. CoRR abs/2309.02285 (2023) - [i63]Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang:
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers. CoRR abs/2309.08532 (2023) - [i62]Dongchao Yang, Jinchuan Tian, Xu Tan, Rongjie Huang, Songxiang Liu, Xuankai Chang, Jiatong Shi, Sheng Zhao, Jiang Bian, Xixin Wu, Zhou Zhao, Shinji Watanabe, Helen Meng:
UniAudio: An Audio Foundation Model Toward Universal Audio Generation. CoRR abs/2310.00704 (2023) - [i61]Han Zhang, Xumeng Wen, Shun Zheng, Wei Xu, Jiang Bian:
Towards Foundation Models for Learning on Tabular Data. CoRR abs/2310.07338 (2023) - [i60]Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu:
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time Series Pretraining. CoRR abs/2310.07402 (2023) - [i59]Jiawen Zhang, Xumeng Wen, Shun Zheng, Jia Li, Jiang Bian:
ProbTS: A Unified Toolkit to Probe Deep Time-series Forecasting. CoRR abs/2310.07446 (2023) - [i58]Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian:
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle. CoRR abs/2310.11249 (2023) - [i57]Dingyao Yu, Kaitao Song, Peiling Lu, Tianyu He, Xu Tan, Wei Ye, Shikun Zhang, Jiang Bian:
MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models. CoRR abs/2310.11954 (2023) - [i56]Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian:
On the Generalization Properties of Diffusion Models. CoRR abs/2311.01797 (2023) - [i55]Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, Han Hu, HsiangTao Wu, Sheng Zhao, Jiang Bian:
GAIA: Zero-shot Talking Avatar Generation. CoRR abs/2311.15230 (2023) - 2022
- [c69]Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian:
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation. AAAI 2022: 4092-4100 - [c68]Yuting Xing, Hangting Ye, Xiaoyu Zhang, Wei Cao, Shun Zheng, Jiang Bian, Yike Guo:
A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. BIBM 2022: 860-863 - [c67]Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, John Lemmon:
A Graph-based Spatiotemporal Model for Energy Markets. CIKM 2022: 4459-4463 - [c66]Zhiping Luo, Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings. COLING 2022: 2598-2607 - [c65]Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tieyan Liu:
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets. ICDM 2022: 21-30 - [c64]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. ICLR 2022 - [c63]Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li:
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble. IJCAI 2022: 3659-3665 - [c62]Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian:
Learning Differential Operators for Interpretable Time Series Modeling. KDD 2022: 1192-1201 - [c61]Xiaozhuang Song, Shun Zheng, Wei Cao, James J. Q. Yu, Jiang Bian:
Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations. NeurIPS 2022 - [c60]Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian:
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction. WWW 2022: 112-121 - [i54]Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian:
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation. CoRR abs/2201.04038 (2022) - [i53]Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. CoRR abs/2202.09340 (2022) - [i52]Lin Huang, Qiyuan Dong, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
AF2: Adaptive Focus Framework for Aerial Imagery Segmentation. CoRR abs/2202.10322 (2022) - [i51]Lin Huang, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting. CoRR abs/2202.10586 (2022) - [i50]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. CoRR abs/2203.07681 (2022) - [i49]Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li:
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble. CoRR abs/2205.09284 (2022) - [i48]Wenlei Shi, Xinquan Huang, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu:
LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data. CoRR abs/2206.09418 (2022) - [i47]Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian, Xiaohan Yi, Shun Zheng, Jian Li:
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures. CoRR abs/2207.01186 (2022) - [i46]Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian:
Learning Differential Operators for Interpretable Time Series Modeling. CoRR abs/2209.01491 (2022) - [i45]Yukun Zheng, Jiang Bian, Guanghao Meng, Chao Zhang, Honggang Wang, Zhixuan Zhang, Sen Li, Tao Zhuang, Qingwen Liu, Xiaoyi Zeng:
Multi-Objective Personalized Product Retrieval in Taobao Search. CoRR abs/2210.04170 (2022) - [i44]Yihan Wu, Junliang Guo, Xu Tan, Chen Zhang, Bohan Li, Ruihua Song, Lei He, Sheng Zhao, Arul Menezes, Jiang Bian:
VideoDubber: Machine Translation with Speech-Aware Length Control for Video Dubbing. CoRR abs/2211.16934 (2022) - [i43]Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian:
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. CoRR abs/2212.01539 (2022) - [i42]Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tieyan Liu:
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets. CoRR abs/2212.02125 (2022) - [i41]Anni Tang, Tianyu He, Xu Tan, Jun Ling, Runnan Li, Sheng Zhao, Li Song, Jiang Bian:
Memories are One-to-Many Mapping Alleviators in Talking Face Generation. CoRR abs/2212.05005 (2022) - [i40]Yuandong Ding, Mingxiao Feng, Guozi Liu, Wei Jiang, Chuheng Zhang, Li Zhao, Lei Song, Houqiang Li, Yan Jin, Jiang Bian:
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management. CoRR abs/2212.07684 (2022) - [i39]Zhujin Gao, Junliang Guo, Xu Tan, Yongxin Zhu, Fang Zhang, Jiang Bian, Linli Xu:
Difformer: Empowering Diffusion Model on Embedding Space for Text Generation. CoRR abs/2212.09412 (2022) - [i38]Zehua Chen, Yihan Wu, Yichong Leng, Jiawei Chen, Haohe Liu, Xu Tan, Yang Cui, Ke Wang, Lei He, Sheng Zhao, Jiang Bian, Danilo P. Mandic:
ResGrad: Residual Denoising Diffusion Probabilistic Models for Text to Speech. CoRR abs/2212.14518 (2022) - 2021
- [j11]Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Demonstration actor critic. Neurocomputing 434: 194-202 (2021) - [j10]Xia Hu, Lingyang Chu, Jian Pei, Weiqing Liu, Jiang Bian:
Model complexity of deep learning: a survey. Knowl. Inf. Syst. 63(10): 2585-2619 (2021) - [j9]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. IEEE Trans. Neural Networks Learn. Syst. 32(4): 1713-1722 (2021) - [c59]Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu:
Universal Trading for Order Execution with Oracle Policy Distillation. AAAI 2021: 107-115 - [c58]Yang Fan, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Xiang-Yang Li:
Learning to Reweight with Deep Interactions. AAAI 2021: 7385-7393 - [c57]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Revisiting the Evaluation of End-to-end Event Extraction. ACL/IJCNLP (Findings) 2021: 4609-4617 - [c56]Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu:
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. AAMAS 2021: 1191-1199 - [c55]Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen, Tie-Yan Liu:
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion. CIKM 2021: 700-709 - [c54]Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, Tie-Yan Liu:
HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. CIKM 2021: 4383-4392 - [c53]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Deep risk model: a deep learning solution for mining latent risk factors to improve covariance matrix estimation. ICAIF 2021: 12:1-12:8 - [c52]Tianhao Zhang, Qiwei Ye, Jiang Bian, Guangming Xie, Tie-Yan Liu:
MFVFD: A Multi-Agent Q-Learning Approach to Cooperative and Non-Cooperative Tasks. IJCAI 2021: 500-506 - [c51]Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu:
Independence-aware Advantage Estimation. IJCAI 2021: 3349-3355 - [c50]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport. KDD 2021: 1017-1026 - [c49]Kingsley Nweye, Zoltán Nagy, Sharada P. Mohanty, Dipam Chakraborty, Siva Sankaranarayanan, Tianzhen Hong, Sourav Dey, Gregor Henze, Ján Drgona, Fangquan Lin, Wei Jiang, Hanwei Zhang, Zhongkai Yi, Jihai Zhang, Cheng Yang, Matthew Motoki, Sorapong Khongnawang, Michael Ibrahim, Abilmansur Zhumabekov, Daniel May, Zhihu Yang, Xiaozhuang Song, Han Zhang, Xiaoning Dong, Shun Zheng, Jiang Bian:
The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. NeurIPS (Competition and Demos) 2021: 85-103 - [c48]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. WWW 2021: 1-10 - [i37]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. CoRR abs/2102.07372 (2021) - [i36]Xia Hu, Lingyang Chu, Jian Pei, Weiqing Liu, Jiang Bian:
Model Complexity of Deep Learning: A Survey. CoRR abs/2103.05127 (2021) - [i35]Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu:
Universal Trading for Order Execution with Oracle Policy Distillation. CoRR abs/2103.10860 (2021) - [i34]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. CoRR abs/2106.09388 (2021) - [i33]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport. CoRR abs/2106.12950 (2021) - [i32]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation. CoRR abs/2107.05201 (2021) - [i31]Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
Instance-wise Graph-based Framework for Multivariate Time Series Forecasting. CoRR abs/2109.06489 (2021) - [i30]Wentao Xu, Weiqing Liu, Lewen Wang, Yingce Xia, Jiang Bian, Jian Yin, Tie-Yan Liu:
HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information. CoRR abs/2110.13716 (2021) - [i29]Zhining Liu, Zhepei Wei, Erxin Yu, Qiang Huang, Kai Guo, Boyang Yu, Zhaonian Cai, Hangting Ye, Wei Cao, Jiang Bian, Pengfei Wei, Jing Jiang, Yi Chang:
IMBENS: Ensemble Class-imbalanced Learning in Python. CoRR abs/2111.12776 (2021) - [i28]Zhining Liu, Pengfei Wei, Zhepei Wei, Boyang Yu, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning. CoRR abs/2111.12791 (2021) - [i27]Wentao Xu, Zhiping Luo, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
KGE-CL: Contrastive Learning of Knowledge Graph Embeddings. CoRR abs/2112.04871 (2021) - [i26]Wentao Xu, Yingce Xia, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
SHGNN: Structure-Aware Heterogeneous Graph Neural Network. CoRR abs/2112.06244 (2021) - 2020
- [c47]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-Segment Activation for Model Compression. AAAI 2020: 6542-6549 - [c46]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. ECCV (1) 2020: 126-144 - [c45]Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. ICDE 2020: 841-852 - [c44]Xia Hu, Weiqing Liu, Jiang Bian, Jian Pei:
Measuring Model Complexity of Neural Networks with Curve Activation Functions. KDD 2020: 1521-1531 - [c43]Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. NeurIPS 2020 - [i25]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. CoRR abs/2005.05650 (2020) - [i24]Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng, Liwei Wang, Jiang Bian, Tie-Yan Liu:
MC-BERT: Efficient Language Pre-Training via a Meta Controller. CoRR abs/2006.05744 (2020) - [i23]Xia Hu, Weiqing Liu, Jiang Bian, Jian Pei:
Measuring Model Complexity of Neural Networks with Curve Activation Functions. CoRR abs/2006.08962 (2020) - [i22]Yang Fan, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Learning to Teach with Deep Interactions. CoRR abs/2007.04649 (2020) - [i21]Xueqing Wu, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Tie-Yan Liu:
Learn to Use Future Information in Simultaneous Translation. CoRR abs/2007.05290 (2020) - [i20]Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu:
Qlib: An AI-oriented Quantitative Investment Platform. CoRR abs/2009.11189 (2020) - [i19]Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. CoRR abs/2010.08830 (2020) - [i18]Hao Wang, Jia Zhang, Yingce Xia, Jiang Bian, Chao Zhang, Tie-Yan Liu:
COSEA: Convolutional Code Search with Layer-wise Attention. CoRR abs/2010.09520 (2020) - [i17]Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian:
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting. CoRR abs/2012.06289 (2020) - [i16]Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu:
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. CoRR abs/2012.13099 (2020)
2010 – 2019
- 2019
- [j8]Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Enhong Chen, Tie-Yan Liu:
Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation. IEEE ACM Trans. Audio Speech Lang. Process. 27(10): 1564-1576 (2019) - [c42]Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Trust Region Evolution Strategies. AAAI 2019: 4352-4359 - [c41]Zichuan Lin, Li Zhao, Jiang Bian, Tao Qin, Guangwen Yang:
Unified Policy Optimization for Robust Reinforcement Learning. ACML 2019: 395-410 - [c40]Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu:
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network. AAMAS 2019: 980-988 - [c39]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. EMNLP/IJCNLP (1) 2019: 337-346 - [c38]Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian:
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction. GlobalSIP 2019: 1-5 - [c37]Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian:
A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies. GlobalSIP 2019: 1-5 - [c36]Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. KDD 2019: 384-394 - [c35]Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu:
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. KDD 2019: 894-902 - [c34]Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu:
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. KDD 2019: 2376-2384 - [c33]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. NeurIPS 2019: 6190-6199 - [i15]Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu:
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network. CoRR abs/1903.00714 (2019) - [i14]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. CoRR abs/1904.07535 (2019) - [i13]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-segment Activation for Model Compression. CoRR abs/1907.06870 (2019) - [i12]Ziyu Liu, Guolin Ke, Jiang Bian, Tie-Yan Liu:
LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm. CoRR abs/1908.09362 (2019) - [i11]Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. CoRR abs/1909.03500 (2019) - [i10]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. CoRR abs/1911.02140 (2019) - 2018
- [c32]Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Guiquan Liu, Tie-Yan Liu:
Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization. AAAI 2018: 5553-5560 - [c31]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning. AAMAS 2018: 721-729 - [c30]Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu:
Investor-Imitator: A Framework for Trading Knowledge Extraction. KDD 2018: 1310-1319 - [c29]Ziniu Hu, Weiqing Liu, Jiang Bian, Xuanzhe Liu, Tie-Yan Liu:
Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction. WSDM 2018: 261-269 - 2017
- [c28]Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu:
Dual Supervised Learning. ICML 2017: 3789-3798 - [c27]Yingce Xia, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Dual Inference for Machine Learning. IJCAI 2017: 3112-3118 - [c26]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. ECML/PKDD (1) 2017: 187-202 - [i9]Yang Fan, Fei Tian, Tao Qin, Jiang Bian, Tie-Yan Liu:
Learning What Data to Learn. CoRR abs/1702.08635 (2017) - [i8]Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu:
Dual Supervised Learning. CoRR abs/1707.00415 (2017) - [i7]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Slim-DP: A Light Communication Data Parallelism for DNN. CoRR abs/1709.09393 (2017) - 2016
- [c25]Huazheng Wang, Fei Tian, Bin Gao, Chengjieren Zhu, Jiang Bian, Tie-Yan Liu:
Solving Verbal Questions in IQ Test by Knowledge-Powered Word Embedding. EMNLP 2016: 541-550 - [i6]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. CoRR abs/1606.00575 (2016) - 2015
- [j7]Bo Long, Jiang Bian, Olivier Chapelle, Ya Zhang, Yoshiyuki Inagaki, Yi Chang:
Active Learning for Ranking through Expected Loss Optimization. IEEE Trans. Knowl. Data Eng. 27(5): 1180-1191 (2015) - [j6]Ting Wang, Shicong Meng, Jiang Bian:
Indexing Earth Mover's Distance over Network Metrics. IEEE Trans. Knowl. Data Eng. 27(6): 1588-1601 (2015) - [j5]Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Hanjun Dai, Tie-Yan Liu:
KNET: A General Framework for Learning Word Embedding Using Morphological Knowledge. ACM Trans. Inf. Syst. 34(1): 4:1-4:25 (2015) - [c24]Bin Gao, Jiang Bian:
DL-WSDM'15: Workshop on Deep Learning for Web Search and Data Mining. WSDM 2015: 421-422 - [i5]Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu:
Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding. CoRR abs/1505.07909 (2015) - 2014
- [j4]Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang:
Exploiting User Preference for Online Learning in Web Content Optimization Systems. ACM Trans. Intell. Syst. Technol. 5(2): 33:1-33:23 (2014) - [c23]Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu:
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. AAAI 2014: 1369-1375 - [c22]Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, Tie-Yan Liu:
RC-NET: A General Framework for Incorporating Knowledge into Word Representations. CIKM 2014: 1219-1228 - [c21]Siyu Qiu, Qing Cui, Jiang Bian, Bin Gao, Tie-Yan Liu:
Co-learning of Word Representations and Morpheme Representations. COLING 2014: 141-150 - [c20]Fei Tian, Hanjun Dai, Jiang Bian, Bin Gao, Rui Zhang, Enhong Chen, Tie-Yan Liu:
A Probabilistic Model for Learning Multi-Prototype Word Embeddings. COLING 2014: 151-160 - [c19]Jiang Bian, Bin Gao, Tie-Yan Liu:
Knowledge-Powered Deep Learning for Word Embedding. ECML/PKDD (1) 2014: 132-148 - [c18]Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu, Tie-Yan Liu:
Sampling dilemma: towards effective data sampling for click prediction in sponsored search. WSDM 2014: 103-112 - [i4]Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu:
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. CoRR abs/1404.5772 (2014) - [i3]Bin Gao, Jiang Bian, Tie-Yan Liu:
WordRep: A Benchmark for Research on Learning Word Representations. CoRR abs/1407.1640 (2014) - [i2]Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Tie-Yan Liu:
Learning Effective Word Embedding using Morphological Word Similarity. CoRR abs/1407.1687 (2014) - 2013
- [j3]Jiang Bian, Anlei Dong, Xiaofeng He, Srihari Reddy, Yi Chang:
User Action Interpretation for Online Content Optimization. IEEE Trans. Knowl. Data Eng. 25(9): 2161-2174 (2013) - [c17]Taifeng Wang, Jiang Bian, Shusen Liu, Yuyu Zhang, Tie-Yan Liu:
Psychological advertising: exploring user psychology for click prediction in sponsored search. KDD 2013: 563-571 - [c16]Yoshiyuki Inagaki, Jiang Bian, Yi Chang:
An effective general framework for localized content optimization. WWW (Companion Volume) 2013: 65-66 - 2012
- [j2]Jiang Bian, Yi Chang, Yun Fu, Wen-Yen Chen:
Learning to blend vitality rankings from heterogeneous social networks. Neurocomputing 97: 390-397 (2012) - [c15]Bo Long, Jiang Bian, Anlei Dong, Yi Chang:
Enhancing product search by best-selling prediction in e-commerce. CIKM 2012: 2479-2482 - [c14]Xiubo Geng, Xin Fan, Jiang Bian, Xin Li, Zhaohui Zheng:
Optimizing user exploring experience in emerging e-commerce products. WWW (Companion Volume) 2012: 23-32 - [c13]Xuanhui Wang, Jiang Bian, Yi Chang, Belle L. Tseng:
Model news relatedness through user comments. WWW (Companion Volume) 2012: 629-630 - [i1]Shuang-Hong Yang, Jiang Bian, Hongyuan Zha:
Hybrid Generative/Discriminative Learning for Automatic Image Annotation. CoRR abs/1203.3530 (2012) - 2011
- [c12]Anlei Dong, Jiang Bian, Xiaofeng He, Srihari Reddy, Yi Chang:
User action interpretation for personalized content optimization in recommender systems. CIKM 2011: 2129-2132 - [c11]Jiang Bian, Yi Chang:
A taxonomy of local search: semi-supervised query classification driven by information needs. CIKM 2011: 2425-2428 - [c10]Yoshiyuki Inagaki, Jiang Bian, Yi Chang, Motoko Maki:
Enhancing mobile search using web search log data. SIGIR 2011: 1201-1202 - 2010
- [c9]Fan Li, Xin Li, Jiang Bian, Zhaohui Zheng:
Optimizing unified loss for web ranking specialization. CIKM 2010: 1593-1596 - [c8]Shuang-Hong Yang, Jiang Bian, Hongyuan Zha:
Hybrid Generative/Discriminative Learning for Automatic Image Annotation. UAI 2010: 683-690 - [c7]Jiang Bian, Tie-Yan Liu, Tao Qin, Hongyuan Zha:
Ranking with query-dependent loss for web search. WSDM 2010: 141-150 - [c6]Jiang Bian, Xin Li, Fan Li, Zhaohui Zheng, Hongyuan Zha:
Ranking specialization for web search: a divide-and-conquer approach by using topical RankSVM. WWW 2010: 131-140
2000 – 2009
- 2009
- [j1]Eugene Agichtein, Yandong Liu, Jiang Bian:
Modeling information-seeker satisfaction in community question answering. ACM Trans. Knowl. Discov. Data 3(2): 10:1-10:27 (2009) - [c5]Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichtein, Hongyuan Zha:
Learning to recognize reliable users and content in social media with coupled mutual reinforcement. WWW 2009: 51-60 - 2008
- [c4]Jiang Bian, Yandong Liu, Eugene Agichtein, Hongyuan Zha:
A few bad votes too many?: towards robust ranking in social media. AIRWeb 2008: 53-60 - [c3]Yandong Liu, Jiang Bian, Eugene Agichtein:
Predicting information seeker satisfaction in community question answering. SIGIR 2008: 483-490 - [c2]Jiang Bian, Yandong Liu, Eugene Agichtein, Hongyuan Zha:
Finding the right facts in the crowd: factoid question answering over social media. WWW 2008: 467-476 - [c1]Ding Zhou, Jiang Bian, Shuyi Zheng, Hongyuan Zha, C. Lee Giles:
Exploring social annotations for information retrieval. WWW 2008: 715-724
Coauthor Index
[j18] [j16] [j14] [c109] [c84] [c77] [c75] [i85] [i68] [c66] [c64] [i53] [i52] [i51] [i50] [i48] [j11] [c59] [c56] [c55] [c54] [c52] [c51] [c48] [i37] [i35] [i31] [i30] [i27] [i26] [c47] [c46] [c45] [i25] [i24] [i22] [i21] [i20] [i18] [i16] [j8] [c42] [c40] [c36] [c35] [c34] [c33] [i15] [i13] [i12] [i11] [i10] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [i9] [i8] [i7] [c25] [i6] [j5] [i5] [c23] [c22] [c21] [c20] [c19] [c18] [i4] [i3] [i2] [c17] [c7]
[i126] [j14] [c104] [c91] [i117] [i114] [i100] [i99] [i96] [i92] [c75] [c74] [i68] [i67] [i65] [i58] [c69] [c66] [c63] [c62] [c60] [i54] [i49] [i46] [j10] [c59] [c58] [c55] [c53] [c50] [c48] [i37] [i36] [i35] [i33] [i32] [i31] [i30] [i27] [i26] [c44] [i23] [i22] [i21] [i20] [i17] [c38] [c37] [c30] [c29]
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