Zhai, Yuexiang

18 publications

ICML 2025 LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models Marwa Abdulhai, Isadora White, Charlie Victor Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine
ICML 2025 SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-Training Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V Le, Sergey Levine, Yi Ma
CPAL 2024 Closed-Loop Transcription via Convolutional Sparse Coding Xili Dai, Ke Chen, Shengbang Tong, Jingyuan Zhang, Xingjian Gao, Mingyang Li, Druv Pai, Yuexiang Zhai, Xiaojun Yuan, Heung-Yeung Shum, Lionel Ni, Yi Ma
CVPR 2024 Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie
NeurIPS 2024 Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine
CPAL 2024 Investigating the Catastrophic Forgetting in Multimodal Large Language Model Fine-Tuning Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma
ICLR 2024 RLIF: Interactive Imitation Learning as Reinforcement Learning Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine
JMLR 2024 White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is? Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma
ICLRW 2023 Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine
ICMLW 2023 Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine
NeurIPSW 2023 Investigating the Catastrophic Forgetting in Multimodal Large Language Models Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma
ICML 2023 Understanding the Complexity Gains of Single-Task RL with a Curriculum Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine
JAIR 2022 Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma
NeurIPS 2022 Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham Kakade, Sergey Levine
NeurIPS 2021 Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
JMLR 2020 Complete Dictionary Learning via L4-Norm Maximization over the Orthogonal Group Yuexiang Zhai, Zitong Yang, Zhenyu Liao, John Wright, Yi Ma
ICLR 2020 Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, Zhihui Zhu
ICLR 2020 Understanding L4-Based Dictionary Learning: Interpretation, Stability, and Robustness Yuexiang Zhai, Hermish Mehta, Zhengyuan Zhou, Yi Ma