| 2025 | ACL | Exploring How Generative MLLMs Perceive More Than CLIP with the Same Vision Encoder. | Siting Li, Pang Wei Koh, Simon Shaolei Du |
| 2025 | AISTATS | Offline Multi-task Transfer RL with Representational Penalization. | Avinandan Bose, Simon Shaolei Du, Maryam Fazel |
| 2025 | CVPR | Is Your World Simulator a Good Story Presenter? A Consecutive Events-Based Benchmark for Future Long Video Generation. | Yiping Wang, Xuehai He, Kuan Wang, Luyao Ma, Jianwei Yang, Shuohang Wang, Simon Shaolei Du, Yelong Shen |
| 2025 | ICLR | The Crucial Role of Samplers in Online Direct Preference Optimization. | Ruizhe Shi, Runlong Zhou, Simon Shaolei Du |
| 2025 | ICML | Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination. | Kunal Jha, Wilka Carvalho, Yancheng Liang, Simon Shaolei Du, Max Kleiman-Weiner, Natasha Jaques |
| 2025 | ICML | Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback. | Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon Shaolei Du, Ruosong Wang |
| 2024 | ICLR | A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning. | Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du |
| 2024 | ICLR | Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking. | Kaifeng Lyu, Jikai Jin, Zhiyuan Li, Simon Shaolei Du, Jason D. Lee, Wei Hu |
| 2024 | ICLR | Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning. | Ruizhe Shi, Yuyao Liu, Yanjie Ze, Simon Shaolei Du, Huazhe Xu |
| 2024 | ICLR | JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention. | Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon Shaolei Du |
| 2024 | ICLR | How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization. | Nuoya Xiong, Lijun Ding, Simon Shaolei Du |
| 2024 | ICLR | Horizon-Free Regret for Linear Markov Decision Processes. | Zihan Zhang, Jason D. Lee, Yuxin Chen, Simon Shaolei Du |
| 2024 | ICLR | Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. | Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du |
| 2024 | ICML | Rethinking Transformers in Solving POMDPs. | Chenhao Lu, Ruizhe Shi, Yuyao Liu, Kaizhe Hu, Simon Shaolei Du, Huazhe Xu |
| 2023 | ICLR | Variance-Aware Sparse Linear Bandits. | Yan Dai, Ruosong Wang, Simon Shaolei Du |
| 2023 | ICLR | Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games. | Shicong Cen, Yuejie Chi, Simon Shaolei Du, Lin Xiao |
| 2023 | ICLR | Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement. | Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du |
| 2023 | ICLR | Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies. | Rui Yuan, Simon Shaolei Du, Robert M. Gower, Alessandro Lazaric, Lin Xiao |
| 2023 | ICML | Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing. | Jikai Jin, Zhiyuan Li, Kaifeng Lyu, Simon Shaolei Du, Jason D. Lee |
| 2023 | ICML | Improved Active Multi-Task Representation Learning via Lasso. | Yiping Wang, Yifang Chen, Kevin Jamieson, Simon Shaolei Du |
| 2023 | ICML | On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness. | Haotian Ye, Xiaoyu Chen, Liwei Wang, Simon Shaolei Du |
| 2023 | ICML | Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes. | Runlong Zhou, Ruosong Wang, Simon Shaolei Du |
| 2023 | ICML | Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments. | Runlong Zhou, Zihan Zhang, Simon Shaolei Du |
| 2022 | AAAI | AdaLoss: A Computationally-Efficient and Provably Convergent Adaptive Gradient Method. | Xiaoxia Wu, Yuege Xie, Simon Shaolei Du, Rachel A. Ward |
| 2022 | ICLR | Provable Adaptation across Multiway Domains via Representation Learning. | Zhili Feng, Shaobo Han, Simon Shaolei Du |
| 2022 | ICLR | A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. | Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du |
| 2021 | ICLR | Optimism in Reinforcement Learning with Generalized Linear Function Approximation. | Yining Wang, Ruosong Wang, Simon Shaolei Du, Akshay Krishnamurthy |
| 2021 | ICLR | Few-Shot Learning via Learning the Representation, Provably. | Simon Shaolei Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei |
| 2021 | ICLR | Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization. | Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Shaolei Du, Yu Wang, Yi Wu |
| 2021 | ICLR | How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks. | Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Shaolei Du, Ken-ichi Kawarabayashi, Stefanie Jegelka |
| 2021 | ICLR | Impact of Representation Learning in Linear Bandits. | Jiaqi Yang, Wei Hu, Jason D. Lee, Simon Shaolei Du |
| 2016 | COLT | An Improved Gap-Dependency Analysis of the Noisy Power Method. | Maria-Florina Balcan, Simon Shaolei Du, Yining Wang, Adams Wei Yu |