Huaxiu Yao (姚骅修)

[1] Peng Xia*, Jianwen Chen*, Hanyang Wang*, Jiaqi Liu, Kaide Zeng, Yu Wang, Siwei Han, Yiyang Zhou, Xujiang Zhao, Haifeng Chen, Zeyu Zheng, Cihang Xie, Huaxiu Yao, SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning, arXiv 2602.08234.

[AI Agent]

[2] Jiaqi Liu*, Yaofeng Su*, Peng Xia, Siwei Han, Zeyu Zheng, Cihang Xie, Mingyu Ding, Huaxiu Yao, SimpleMem: Efficient Lifelong Memory for LLM Agents, arXiv 2601.02553.

[AI Agent]

[3] Peng Xia, Kaide Zeng, Jiaqi Liu, Can Qin, Fang Wu, Yiyang Zhou, Caiming Xiong, Huaxiu Yao, Agent0: Unleashing self-evolving agents from zero data via tool-integrated reasoning, arXiv 2511.16043.

[AI Agent]

[4] Zhaoyang Wang, Canwen Xu, Boyi Liu, Yite Wang, Siwei Han, Zhewei Yao, Huaxiu Yao^†, Yuxiong He^†, Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning, arXiv 2602.10090.

[AI Agent]

[5] Siwei Han, Kaiwen Xiong, Jiaqi Liu, Xinyu Ye, Yaofeng Su, Wenbo Duan, Xinyuan Liu, Cihang Xie, Mohit Bansal, Mingyu Ding, Linjun Zhang, Huaxiu Yao, Alignment Tipping Process: How Self-Evolution Pushes LLM Agents Off the Rails, arXiv 2510.04860.

[AI Agent]

[6] Yiyang Zhou*, Haoqin Tu*, Zijun Wang, Zeyu Wang, Niklas Muennighoff, Fan Nie, Yejin Choi, James Zou, Chaorui Deng, Shen Yan, Haoqi Fan, Cihang Xie, Huaxiu Yao^†, Qinghao Ye^†, When visualizing is the first step to reasoning: Mira, a benchmark for visual chain-of-thought, arXiv:2511.02779.

[VLM/VLA] [Benchmark & Evaluation]

[7] Fan Nie, Ken Ziyu Liu, Zihao Wang, Rui Sun, Wei Liu, Weijia Shi, Huaxiu Yao, Linjun Zhang, Andrew Y Ng, James Zou, Sanmi Koyejo, Yejin Choi, Percy Liang, Niklas Muennighoff, Uq: Assessing language models on unsolved questions, arXiv:2508.17580.

[Benchmark & Evaluation]

[8] Zijian Zhang*, Kaiyuan Zheng*, Zhaorun Chen*, Joel Jang, Yi Li, Siwei Han, Chaoqi Wang, Mingyu Ding, Dieter Fox, Huaxiu Yao, Grape: Generalizing robot policy via preference alignment, in Proceeding of 2026 IEEE International Conference on Robotics and Automation (ICRA 2026), Vienna, Austria, Jun 2026.

[VLM/VLA]

[9] Xinyu Geng*, Peng Xia*, Zhen Zhang, Xinyu Wang, Qiuchen Wang, Ruixue Ding, Chenxi Wang, Jialong Wu, Yida Zhao, Kuan Li, Yong Jiang, Pengjun Xie, Fei Huang, Huaxiu Yao, Yi R. Feng, Jingren Zhou, Webwatcher: Breaking new frontier of vision-language deep research agent, in Proceeding of the 14th International Conference on Learning Representations (ICLR 2026), Rio de Janeiro, Brazil, Apr 2026.

[AI Agent] [VLM/VLA]

[10] Yiyang Zhou*, Yangfan He*, Yaofeng Su, Siwei Han, Joel Jang, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding, in Proceeding of the Thirty-Ninth Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, CA, Dec 2025.

[AI Agent] [VLM/VLA]

[11] Haibo Tong*, Zhaoyang Wang*, Zhaorun Chen, Haonian Ji, Shi Qiu, Siwei Han, Kexin Geng, Zhongkai Xue, Yiyang Zhou, Peng Xia, Mingyu Ding, Rafael Rafailov, Chelsea Finn, Huaxiu Yao, MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation, in Proceeding of the Thirty-Ninth Conference on Neural Information Processing Systems (NeurIPS 2025, Spotlight), San Diego, CA, Dec 2025.

[VLM/VLA] [Benchmark & Evaluation]

[12] 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?, in Proceeding of the Thirty-Ninth Conference on Neural Information Processing Systems Track on Datasets & Benchmarks (NeurIPS 2025), San Diego, CA, Dec 2025.

[VLM/VLA] [Benchmark & Evaluation]

[13] Yiyang Zhou*, Zhaoyang Wang*, Tianle Wang*, Shangyu Xing, Peng Xia, Bo Li, Kaiyuan Zheng, Zijian Zhang, Zhaorun Chen, Wenhao Zheng, Xuchao Zhang, Chetan Bansal, Weitong Zhang, Ying Wei, Mohit Bansal, Huaxiu Yao, AnyPrefer: An Automatic Framework for Preference Data Synthesis, in Proceeding of the 13th International Conference on Learning Representations (ICLR 2025), Singapore, Apr 2025.

[AI Agent] [VLM/VLA] [Benchmark & Evaluation]

[14] 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, in Proceeding of the Thirty-Eighth Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec 2024.

[VLM/VLA]

[15] Yiyang Zhou*, Chenhang Cui*, Rafael Rafailov, Chelsea Finn, Huaxiu Yao, Aligning modalities in vision large language models via preference fine-tuning, arXiv:2402.11411.

[VLM/VLA]

[16] 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, in Proceeding of the 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024.

[VLM/VLA]

[17] 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, in Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, Dec. 2023.

[18] Percy Liang, Rishi Bommasani, Tony Lee, [and 47 others, including Huaxiu Yao], Holistic Evaluation of Language Models, Transactions on Machine Learning Research (TMLR, Featured), 2023. (Outstanding Paper Award)

[Benchmark & Evaluation]

[1] Siwei Han, Peng Xia, Ruiyi Zhang, Tong Sun, Yun Li, Hongtu Zhu, Huaxiu Yao, MDocAgent: A Multi-Modal Multi-Agent Framework for Document Understanding, arXiv 2503.13964.

[FM for Document Processing]

[2] Peng Xia*, Jinglu Wang*, Yibo Peng*, Kaide Zeng, Xian Wu, Xiangru Tang, Hongtu Zhu, Yun Li, Shujie Liu, Yan Lu^†, Huaxiu Yao^†, MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning, in Proceeding of the 14th International Conference on Learning Representations (ICLR 2026), Rio de Janeiro, Brazil, Apr 2026.

[FM for Health]

[3] Haonian Ji*, Shi Qiu*, Siyang Xin*, Siwei Han*, Zhaorun Chen, Hongyi Wang, Dake Zhang, Huaxiu Yao, From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization, in Proceeding of the 14th International Conference on Learning Representations (ICLR 2026), Rio de Janeiro, Brazil, Apr 2026.

[FM for Education]

[4] Kangyu Zhu*, Peng Xia*, Yun Li, Hongtu Zhu, Sheng Wang, Huaxiu Yao, MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization, in Proceeding of the Forty-second International Conference on Machine Learning (ICML 2025), Vancouver, Canada, Jul 2025. [arXiv] [Code]

[FM for Health]

[5] 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, in Proceeding of the 13th International Conference on Learning Representations (ICLR 2025), Singapore, Apr 2025. [arXiv] [Code]

[FM for Health]

[6] 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, in Proceeding of the Thirty-Eighth Conference on Neural Information Processing Systems Track on Datasets & Benchmarks (NeurIPS 2024), Vancouver, Canada, Dec 2024.

[FM for Health]

[7] 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, in Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, Nov. 2024.

[FM for Health]

• International Conference on Machine Learning (ICML), 2024
• Conference on Neural Information Processing Systems (NeurIPS), 2024; D&B Track (2022 - 2024)
• International Conference on Learning Representations (ICLR), 2025
• International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
• Empirical Methods in Natural Language Processing  (EMNLP), 2024
• International Conference on Automated Machine Learning (AutoML-Conf), 2022 - 2024
• Learning on Graphs Conference (LoG), 2022 - 2024

• Organizer, Workshop on Foundation Models in the Wild, ICML 2024 (Co-organizers: Xinyu Yang, Bilge Acun, Kamalika Chaudhuri, Beidi Chen, Giulia Fanti, Junlin Han, Lianhui Qin, Shengbang Tong, Philip Torr, Hao Wang, Cathy Wu, James Zou)
• Lead Organizer, Workshop on Reliable and Responsible Foundation Models, ICLR 2024 (Co-organizers: Mohit Bansal, Zhun Deng, Chelsea Finn, Pavel Izmailov, He He, Pang Wei Koh, Eric Mitchell, Cihang Xie) [Website]
• Lead Organizer, Sixth Workshop on Meta-Learning, NeurIPS 2022 (Co-organizers: Fábio Ferreira, Frank Hutter, Joaquin Vanschoren, Eleni Triantafillou, Qi Lei) [Website]
• Lead Organizer, the First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward, ICML 2022 (Co-organizers: Hugo Larochelle, Colin Rafel, Percy Liang, Jian Tang, Ying Wei, Saining Xie, Eric P. Xing, Chelsea Finn) [Website]
• Organizer, Fifth Workshop on Meta-Learning, NeurIPS 2021 (Co-organizers: Fábio Ferreira, Erin Grant, Frank Hutter, Jonathan Schwarz, Joaquin Vanschoren) [Website]