Learning to Reconstruct 3D Manhattan Wireframes From a Single Image. - Yichao Zhou 003; Haozhi Qi; Yuexiang Zhai; Qi Sun 003; Zhili Chen; Li-Yi Wei; Yi Ma 001 (ICCV, 2019)

Complete Dictionary Learning via 𝓁4-Norm Maximization over the Orthogonal Group. - Yuexiang Zhai; Zitong Yang; Zhenyu Liao 003; John Wright 001; Yi Ma 001 (CoRR, 2019)

Analysis of the Optimization Landscapes for Overcomplete Representation Learning. - Qing Qu 001; Yuexiang Zhai; Xiao Li 009; Yuqian Zhang; Zhihui Zhu (CoRR, 2019)

Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning. - Qing Qu 001; Yuexiang Zhai; Xiao Li 009; Yuqian Zhang; Zhihui Zhu (ICLR, 2020)

Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness. - Yuexiang Zhai; Hermish Mehta; Zhengyuan Zhou; Yi Ma 001 (ICLR, 2020)

Complete Dictionary Learning via L4-Norm Maximization over the Orthogonal Group. - Yuexiang Zhai; Zitong Yang; Zhenyu Liao 003; John Wright 001; Yi Ma 001 (J. Mach. Learn. Res., 2020)

Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. - Sheng Liu; Xiao Li 026; Yuexiang Zhai; Chong You; Zhihui Zhu; Carlos Fernandez-Granda; Qing Qu 001 (NeurIPS, 2021)

Computational Benefits of Intermediate Rewards for Hierarchical Planning. - Yuexiang Zhai; Christina Baek; Zhengyuan Zhou; Jiantao Jiao; Yi Ma 001 (CoRR, 2021)

Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. - Abhishek Gupta 004; Aldo Pacchiano; Yuexiang Zhai; Sham M. Kakade; Sergey Levine (NeurIPS, 2022)

Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. - Yuexiang Zhai; Christina Baek; Zhengyuan Zhou; Jiantao Jiao; Yi Ma 001 (J. Artif. Intell. Res., 2022)

Understanding the Complexity Gains of Single-Task RL with a Curriculum. - Qiyang Li; Yuexiang Zhai; Yi Ma 001; Sergey Levine (ICML, 2023)

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning. - Mitsuhiko Nakamoto; Yuexiang Zhai; Anikait Singh; Max Sobol Mark; Yi Ma 001; Chelsea Finn; Aviral Kumar; Sergey Levine (CoRR, 2023)

Investigating the Catastrophic Forgetting in Multimodal Large Language Models. - Yuexiang Zhai; Shengbang Tong; Xiao Li 022; Mu Cai; Qing Qu 001; Yong Jae Lee; Yi Ma 001 (CoRR, 2023)

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 001 (CoRR, 2023)

LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models. - Marwa Abdulhai; Isadora White; Charlie Snell; Charles Sun; Joey Hong; Yuexiang Zhai; Kelvin Xu; Sergey Levine (CoRR, 2023)

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 002; Heung-Yeung Shum; Lionel M. Ni; Yi Ma 001 (CPAL, 2024)

Investigating the Catastrophic Forgetting in Multimodal Large Language Model Fine-Tuning. - Yuexiang Zhai; Shengbang Tong; Xiao Li 022; Mu Cai; Qing Qu 001; Yong Jae Lee; Yi Ma 001 (CPAL, 2024)

Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. - Shengbang Tong; Zhuang Liu 003; Yuexiang Zhai; Yi Ma 001; Yann LeCun; Saining Xie (CVPR, 2024)

RLIF: Interactive Imitation Learning as Reinforcement Learning. - Jianlan Luo; Perry Dong; Yuexiang Zhai; Yi Ma 001; Sergey Levine (ICLR, 2024)

Is Offline Decision Making Possible with Only Few Samples? Reliable Decisions in Data-Starved Bandits via Trust Region Enhancement. - Ruiqi Zhang; Yuexiang Zhai; Andrea Zanette (CoRR, 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 001; Sergey Levine (CoRR, 2024)

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 001 (CoRR, 2025)

Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs. - Chun-Hsiao Yeh; Chenyu Wang; Shengbang Tong; Ta Ying Cheng; Ruoyu Wang 014; Tianzhe Chu; Yuexiang Zhai; Yubei Chen; Shenghua Gao; Yi Ma 001 (CoRR, 2025)