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Journal Articles
- 2022
[j2]Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma:
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. J. Artif. Intell. Res. 73: 847-896 (2022)- 2020
- [j1]Yuexiang Zhai, Zitong Yang, Zhenyu Liao, John Wright, Yi Ma:
Complete Dictionary Learning via L4-Norm Maximization over the Orthogonal Group. J. Mach. Learn. Res. 21: 165:1-165:68 (2020)
Conference and Workshop Papers
- 2024
- [c8]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CVPR 2024: 9568-9578 - [c7]Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine:
RLIF: Interactive Imitation Learning as Reinforcement Learning. ICLR 2024 - 2023
- [c6]Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine:
Understanding the Complexity Gains of Single-Task RL with a Curriculum. ICML 2023: 20412-20451 - 2022
- [c5]Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine:
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. NeurIPS 2022 - 2021
- [c4]Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu:
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. NeurIPS 2021: 28919-28928 - 2020
- [c3]Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang
, Zhihui Zhu:
Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning. ICLR 2020 - [c2]Yuexiang Zhai, Hermish Mehta, Zhengyuan Zhou, Yi Ma:
Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness. ICLR 2020 - 2019
- [c1]Yichao Zhou, Haozhi Qi, Yuexiang Zhai, Qi Sun, Zhili Chen, Li-Yi Wei, Yi Ma:
Learning to Reconstruct 3D Manhattan Wireframes From a Single Image. ICCV 2019: 7697-7706
Informal and Other Publications
- 2024
- [i16]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CoRR abs/2401.06209 (2024) - [i15]Ruiqi Zhang, Yuexiang Zhai, Andrea Zanette:
Is Offline Decision Making Possible with Only Few Samples? Reliable Decisions in Data-Starved Bandits via Trust Region Enhancement. CoRR abs/2402.15703 (2024) - [i14]Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine:
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. CoRR abs/2405.10292 (2024) - 2023
- [i13]Xili Dai, Ke Chen, Shengbang Tong, Jingyuan Zhang, Xingjian Gao, Mingyang Li, Druv Pai, Yuexiang Zhai, Xiaojun Yuan, Heung-Yeung Shum, Lionel M. Ni, Yi Ma:
Closed-Loop Transcription via Convolutional Sparse Coding. CoRR abs/2302.09347 (2023) - [i12]Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine:
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning. CoRR abs/2303.05479 (2023) - [i11]Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma:
Investigating the Catastrophic Forgetting in Multimodal Large Language Models. CoRR abs/2309.10313 (2023) - [i10]Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine:
RLIF: Interactive Imitation Learning as Reinforcement Learning. CoRR abs/2311.12996 (2023) - [i9]Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma:
White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is? CoRR abs/2311.13110 (2023) - [i8]Marwa Abdulhai, Isadora White, Charlie Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine:
LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models. CoRR abs/2311.18232 (2023) - 2022
- [i7]Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine:
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. CoRR abs/2210.09579 (2022) - [i6]Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine:
Understanding the Complexity Gains of Single-Task RL with a Curriculum. CoRR abs/2212.12809 (2022) - 2021
- [i5]Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu:
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. CoRR abs/2103.00673 (2021) - [i4]Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma:
Computational Benefits of Intermediate Rewards for Hierarchical Planning. CoRR abs/2107.03961 (2021) - 2019
- [i3]Yichao Zhou, Haozhi Qi, Yuexiang Zhai, Qi Sun, Zhili Chen, Li-Yi Wei, Yi Ma:
Learning to Reconstruct 3D Manhattan Wireframes from a Single Image. CoRR abs/1905.07482 (2019) - [i2]Yuexiang Zhai, Zitong Yang, Zhenyu Liao, John Wright, Yi Ma:
Complete Dictionary Learning via 𝓁4-Norm Maximization over the Orthogonal Group. CoRR abs/1906.02435 (2019) - [i1]Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, Zhihui Zhu:
Analysis of the Optimization Landscapes for Overcomplete Representation Learning. CoRR abs/1912.02427 (2019)
Coauthor Index
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