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2020 – today
- 2024
[j7]Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn:
Conservative Prediction via Data-Driven Confidence Minimization. Trans. Mach. Learn. Res. 2024 (2024)- [c54]Huaxiu Yao:
Towards Reliable Learning in the Wild: Generalization and Adaptation. AAAI 2024: 22683 - [c53]Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Fuxiao Liu, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, Furong Huang:
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. ACL (1) 2024: 416-442 - [c52]Xiaohui Zhang, Jaehong Yoon, Mohit Bansal, Huaxiu Yao:
Multimodal Representation Learning by Alternating Unimodal Adaptation. CVPR 2024: 27446-27456 - [c51]Haoqin Tu, Chenhang Cui, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, Cihang Xie:
How Many Are in This Image A Safety Evaluation Benchmark for Vision LLMs. ECCV (51) 2024: 37-55 - [c50]Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao:
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. EMNLP 2024: 1081-1093 - [c49]Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn:
Fine-Tuning Language Models for Factuality. ICLR 2024 - [c48]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Improving Domain Generalization with Domain Relations. ICLR 2024 - [c47]Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao:
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR 2024 - [c46]Zhaorun Chen, Zhuokai Zhao, Hongyin Luo, Huaxiu Yao, Bo Li, Jiawei Zhou:
HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding. ICML 2024 - [c45]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c44]Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei:
Conformal Prediction for Deep Classifier via Label Ranking. ICML 2024 - [c43]Xu Yang, Huaxiu Yao, Ying Wei:
One Meta-tuned Transformer is What You Need for Few-shot Learning. ICML 2024 - [c42]Zhen-Yu Zhang, Siwei Han, Huaxiu Yao, Gang Niu, Masashi Sugiyama:
Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought. ICML 2024 - [c41]Viet Duong
, Qiong Wu, Zhengyi Zhou, Hongjue Zhao, Chenxiang Luo, Eric Zavesky, Huaxiu Yao, Huajie Shao:
CAT: Interpretable Concept-based Taylor Additive Models. KDD 2024: 723-734 - [c40]Peng Xia, Ming Hu, Feilong Tang, Wenxue Li, Wenhao Zheng, Lie Ju, Peibo Duan, Huaxiu Yao, Zongyuan Ge:
Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations. MICCAI (10) 2024: 427-437 - [c39]Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu, Ruiqi Zhang, Xiang Li, Bhiksha Raj, Huaxiu Yao:
AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition. NAACL-HLT 2024: 1346-1362 - [i74]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i73]Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, Furong Huang:
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. CoRR abs/2401.10529 (2024) - [i72]Wenhao Zheng, Dongsheng Peng, Hongxia Xu, Hongtu Zhu, Tianfan Fu, Huaxiu Yao:
Multimodal Clinical Trial Outcome Prediction with Large Language Models. CoRR abs/2402.06512 (2024) - [i71]Zhen-Yu Zhang, Siwei Han, Huaxiu Yao, Gang Niu, Masashi Sugiyama:
Generating Chain-of-Thoughts with a Direct Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought. CoRR abs/2402.06918 (2024) - [i70]Zongbo Han, Yifeng Yang, Changqing Zhang, Linjun Zhang, Joey Tianyi Zhou, Qinghua Hu, Huaxiu Yao:
Selective Learning: Towards Robust Calibration with Dynamic Regularization. CoRR abs/2402.08384 (2024) - [i69]Yiyang Zhou, Chenhang Cui, Rafael Rafailov, Chelsea Finn, Huaxiu Yao:
Aligning Modalities in Vision Large Language Models via Preference Fine-tuning. CoRR abs/2402.11411 (2024) - [i68]Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu, Ruiqi Zhang, Xiang Li, Bhiksha Raj, Huaxiu Yao:
AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition. CoRR abs/2402.11452 (2024) - [i67]Zhiyuan Wang, Jinhao Duan, Chenxi Yuan, Qingyu Chen, Tianlong Chen, Huaxiu Yao, Yue Zhang, Ren Wang, Kaidi Xu, Xiaoshuang Shi:
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond. CoRR abs/2402.14259 (2024) - [i66]Taixi Lu, Haoyu Wang, Huajie Shao, Jing Gao, Huaxiu Yao:
C3: Confidence Calibration Model Cascade for Inference-Efficient Cross-Lingual Natural Language Understanding. CoRR abs/2402.15991 (2024) - [i65]Qichuan Yin, Junzhou Huang, Huaxiu Yao, Linjun Zhang:
Distribution-Free Fair Federated Learning with Small Samples. CoRR abs/2402.16158 (2024) - [i64]Zhaorun Chen, Zhuokai Zhao, Hongyin Luo, Huaxiu Yao, Bo Li, Jiawei Zhou:
HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding. CoRR abs/2403.00425 (2024) - [i63]Zhongwei Wan, Che Liu, Xin Wang, Chaofan Tao, Hui Shen, Zhenwu Peng, Jie Fu, Rossella Arcucci, Huaxiu Yao, Mi Zhang:
Electrocardiogram Instruction Tuning for Report Generation. CoRR abs/2403.04945 (2024) - [i62]Haoran Li, Junqi Liu, Zexian Wang, Shiyuan Luo, Xiaowei Jia, Huaxiu Yao:
LITE: Modeling Environmental Ecosystems with Multimodal Large Language Models. CoRR abs/2404.01165 (2024) - [i61]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. CoRR abs/2405.14622 (2024) - [i60]Xiyao Wang, Jiuhai Chen, Zhaoyang Wang, Yuhang Zhou, Yiyang Zhou, Huaxiu Yao, Tianyi Zhou, Tom Goldstein, Parminder Bhatia, Furong Huang, Cao Xiao:
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. CoRR abs/2405.15973 (2024) - [i59]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 Zou, Huaxiu Yao:
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. CoRR abs/2406.06007 (2024) - [i58]Peng Xia, Ming Hu, Feilong Tang, Wenxue Li, Wenhao Zheng, Lie Ju, Peibo Duan, Huaxiu Yao, Zongyuan Ge:
Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations. CoRR abs/2406.06384 (2024) - [i57]Taiming Lu, Lingfeng Shen, Xinyu Yang, Weiting Tan, Beidi Chen, Huaxiu Yao:
It Takes Two: On the Seamlessness between Reward and Policy Model in RLHF. CoRR abs/2406.07971 (2024) - [i56]Viet Duong, Qiong Wu, Zhengyi Zhou, Hongjue Zhao, Chenxiang Luo, Eric Zavesky, Huaxiu Yao, Huajie Shao:
CAT: Interpretable Concept-based Taylor Additive Models. CoRR abs/2406.17931 (2024) - [i55]Zhaorun Chen, Yichao Du, Zichen Wen, Yiyang Zhou, Chenhang Cui, Zhenzhen Weng, Haoqin Tu, Chaoqi Wang, Zhengwei Tong, Qinglan Huang, Canyu Chen, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, Huaxiu Yao:
MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation? CoRR abs/2407.04842 (2024) - [i54]Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao:
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. CoRR abs/2407.05131 (2024) - [i53]Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu:
Can Editing LLMs Inject Harm? CoRR abs/2407.20224 (2024) - [i52]Weiliang Tang, Jia-Hui Pan, Wei Zhan, Jianshu Zhou, Huaxiu Yao, Yun-Hui Liu, Masayoshi Tomizuka, Mingyu Ding, Chi-Wing Fu:
Embodiment-Agnostic Action Planning via Object-Part Scene Flow. CoRR abs/2409.10032 (2024) - [i51]Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang:
NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models. CoRR abs/2410.01870 (2024) - [i50]Zhen-Yu Zhang, Jiandong Zhang, Huaxiu Yao, Gang Niu, Masashi Sugiyama:
On Unsupervised Prompt Learning for Classification with Black-box Language Models. CoRR abs/2410.03124 (2024) - [i49]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. CoRR abs/2410.07112 (2024) - [i48]Peng Xia, Siwei Han, Shi Qiu, Yiyang Zhou, Zhaoyang Wang, Wenhao Zheng, Zhaorun Chen, Chenhang Cui, Mingyu Ding, Linjie Li, Lijuan Wang, Huaxiu Yao:
MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models. CoRR abs/2410.10139 (2024) - [i47]Zhaoyang Wang, Weilei He, Zhiyuan Liang, Xuchao Zhang, Chetan Bansal, Ying Wei, Weitong Zhang, Huaxiu Yao:
CREAM: Consistency Regularized Self-Rewarding Language Models. CoRR abs/2410.12735 (2024) - [i46]Jaehong Yoon, Shoubin Yu, Vaidehi Patil, Huaxiu Yao, Mohit Bansal:
SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation. CoRR abs/2410.12761 (2024) - [i45]Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao:
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models. CoRR abs/2410.13085 (2024) - [i44]Chenhang Cui, An Zhang, Yiyang Zhou, Zhaorun Chen, Gelei Deng, Huaxiu Yao, Tat-Seng Chua:
Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment. CoRR abs/2410.14148 (2024) - [i43]Taneesh Gupta, Shivam Shandilya, Xuchao Zhang, Supriyo Ghosh, Chetan Bansal, Huaxiu Yao, Saravan Rajmohan:
Unveiling Context-Aware Criteria in Self-Assessing LLMs. CoRR abs/2410.21545 (2024) - 2023
- [j6]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023) - [j5]Xinyu Yang, Huaxiu Yao, Allan Zhou, Chelsea Finn:
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations. Trans. Mach. Learn. Res. 2023 (2023) - [c38]Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning:
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. EMNLP 2023: 5433-5442 - [c37]Haoyu Wang, Yaqing Wang, Huaxiu Yao, Jing Gao:
Macedon: Minimizing Representation Coding Rate Reduction for Cross-Lingual Natural Language Understanding. EMNLP (Findings) 2023: 12426-12436 - [c36]Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn:
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. ICLR 2023 - [c35]Yoonho Lee, Huaxiu Yao, Chelsea Finn:
Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement. ICLR 2023 - [c34]Xinzhe Zuo, Zixiang Chen, Huaxiu Yao, Yuan Cao, Quanquan Gu:
Understanding Train-Validation Split in Meta-Learning with Neural Networks. ICLR 2023 - [c33]Yunzhe Qi, Yikun Ban, Tianxin Wei, Jiaru Zou, Huaxiu Yao, Jingrui He:
Meta-Learning with Neural Bandit Scheduler. NeurIPS 2023 - [c32]Zhenbang Wu, Huaxiu Yao, David M. Liebovitz, Jimeng Sun:
An Iterative Self-Learning Framework for Medical Domain Generalization. NeurIPS 2023 - [i42]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Leveraging Domain Relations for Domain Generalization. CoRR abs/2302.02609 (2023) - [i41]Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou:
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. CoRR abs/2304.03935 (2023) - [i40]Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning:
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. CoRR abs/2305.14975 (2023) - [i39]Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn:
Conservative Prediction via Data-Driven Confidence Minimization. CoRR abs/2306.04974 (2023) - [i38]Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao:
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. CoRR abs/2310.00754 (2023) - [i37]Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei:
Conformal Prediction for Deep Classifier via Label Ranking. CoRR abs/2310.06430 (2023) - [i36]Chenhang Cui, Yiyang Zhou, Xinyu Yang, Shirley Wu, Linjun Zhang, James Zou, Huaxiu Yao:
Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges. CoRR abs/2311.03287 (2023) - [i35]Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn:
Fine-tuning Language Models for Factuality. CoRR abs/2311.08401 (2023) - [i34]Haoqiang Kang, Juntong Ni, Huaxiu Yao:
Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification. CoRR abs/2311.09114 (2023) - [i33]Shiyuan Luo, Juntong Ni, Shengyu Chen, Runlong Yu, Yiqun Xie, Licheng Liu, Zhenong Jin, Huaxiu Yao, Xiaowei Jia:
FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems. CoRR abs/2311.10255 (2023) - [i32]Xiaohui Zhang, Jaehong Yoon, Mohit Bansal, Huaxiu Yao:
Multimodal Representation Learning by Alternating Unimodal Adaptation. CoRR abs/2311.10707 (2023) - [i31]Haoqin Tu, Chenhang Cui, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, Cihang Xie:
How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs. CoRR abs/2311.16101 (2023) - 2022
- [c31]Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang:
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation. ACL (1) 2022: 583-595 - [c30]Huaxiu Yao, Linjun Zhang, Chelsea Finn:
Meta-Learning with Fewer Tasks through Task Interpolation. ICLR 2022 - [c29]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. ICML 2022: 25407-25437 - [c28]Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang:
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer. KDD 2022: 1162-1172 - [c27]Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn:
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. NeurIPS 2022 - [c26]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. NeurIPS 2022 - [c25]Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu:
GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy. NeurIPS 2022 - [i30]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. CoRR abs/2201.00299 (2022) - [i29]Yoonho Lee, Huaxiu Yao, Chelsea Finn:
Diversify and Disambiguate: Learning From Underspecified Data. CoRR abs/2202.03418 (2022) - [i28]Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang:
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation. CoRR abs/2203.11670 (2022) - [i27]Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang:
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer. CoRR abs/2205.13947 (2022) - [i26]Zhenbang Wu, Huaxiu Yao, Zhe Su, David M. Liebovitz, Lucas M. Glass, James Zou, Chelsea Finn, Jimeng Sun:
Knowledge-Driven New Drug Recommendation. CoRR abs/2210.05572 (2022) - [i25]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. CoRR abs/2210.05775 (2022) - [i24]Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn:
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. CoRR abs/2210.11466 (2022) - [i23]Huaxiu Yao, Xinyu Yang, Allan Zhou, Chelsea Finn:
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations. CoRR abs/2210.14358 (2022) - [i22]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - [i21]Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn:
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. CoRR abs/2211.14238 (2022) - 2021
- [j4]Yanwei Yu, Xianfeng Tang, Huaxiu Yao, Xiuwen Yi, Zhenhui Li:
Citywide Traffic Volume Inference with Surveillance Camera Records. IEEE Trans. Big Data 7(6): 900-912 (2021) - [j3]Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla:
Inductive Contextual Relation Learning for Personalization. ACM Trans. Inf. Syst. 39(3): 35:1-35:22 (2021) - [c24]Porter Jenkins, Ahmad Farag, J. Stockton Jenkins, Huaxiu Yao, Suhang Wang, Zhenhui Li:
Neural Utility Functions. AAAI 2021: 7917-7925 - [c23]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. EMNLP (1) 2021: 1814-1821 - [c22]Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li:
Improving Generalization in Meta-learning via Task Augmentation. ICML 2021: 11887-11897 - [c21]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. NeurIPS 2021: 7497-7509 - [c20]Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Li:
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery. NeurIPS 2021: 8256-8268 - [c19]Jiatu Shi, Huaxiu Yao, Xian Wu, Tong Li, Zedong Lin, Tengfei Wang, Binqiang Zhao:
Relation-aware Meta-learning for E-commerce Market Segment Demand Prediction with Limited Records. WSDM 2021: 220-228 - [i20]Huaxiu Yao, Linjun Zhang, Chelsea Finn:
Meta-Learning with Fewer Tasks through Task Interpolation. CoRR abs/2106.02695 (2021) - [i19]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. CoRR abs/2109.04707 (2021) - [i18]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. CoRR abs/2110.14057 (2021) - 2020
- [c18]Xinshi Zang, Huaxiu Yao, Guanjie Zheng, Nan Xu, Kai Xu, Zhenhui Li:
MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control. AAAI 2020: 1153-1160 - [c17]Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla:
Few-Shot Knowledge Graph Completion. AAAI 2020: 3041-3048 - [c16]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. AAAI 2020: 5956-5963 - [c15]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-Shot Learning via Knowledge Transfer. AAAI 2020: 6656-6663 - [c14]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks. CIKM 2020: 1435-1444 - [c13]Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li:
Automated Relational Meta-learning. ICLR 2020 - [c12]Huaxiu Yao, Xiaowei Jia, Vipin Kumar, Zhenhui Li:
Learning with Small Data. KDD 2020: 3539-3540 - [c11]Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong:
Online Structured Meta-learning. NeurIPS 2020 - [c10]Xianfeng Tang, Yandong Li, Yiwei Sun, Huaxiu Yao, Prasenjit Mitra, Suhang Wang:
Transferring Robustness for Graph Neural Network Against Poisoning Attacks. WSDM 2020: 600-608 - [c9]Zhenhui Li, Huaxiu Yao, Fenglong Ma:
Learning with Small Data. WSDM 2020: 884-887 - [i17]Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li:
Automated Relational Meta-learning. CoRR abs/2001.00745 (2020) - [i16]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Graph Convolutional Networks against Degree-Related Biases. CoRR abs/2006.15643 (2020) - [i15]Huaxiu Yao, Longkai Huang, Ying Wei, Li Tian, Junzhou Huang, Zhenhui Li:
Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning. CoRR