| 2026 | CAV | The Simulator's Blueprint: Automata Learning from Cybersecurity Logs. | Tudor Braicu, Benjamin Ylvisaker, Nicolas A. Espinosa Dice, Yiding Chen, Yiyi Zhang, Nate Foster, Hossein Hojjat |
| 2025 | ICLR | Diffusing States and Matching Scores: A New Framework for Imitation Learning. | Runzhe Wu, Yiding Chen, Gokul Swamy, Kiant Brantley, Wen Sun |
| 2025 | ICML | Convergence of Consistency Model with Multistep Sampling under General Data Assumptions. | Yiding Chen, Yiyi Zhang, Owen Oertell, Wen Sun |
| 2025 | ICML | Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution. | Alex Clinton, Yiding Chen, Jerry Zhu, Kirthevasan Kandasamy |
| 2024 | AAAI | Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption. | Yiding Chen, Xuezhou Zhang, Qiaomin Xie, Xiaojin Zhu |
| 2024 | ICML | Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. | Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Jerry Zhu, Qiaomin Xie |
| 2023 | AISTATS | Byzantine-Robust Online and Offline Distributed Reinforcement Learning. | Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu |
| 2022 | AISTATS | Corruption-robust Offline Reinforcement Learning. | Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun |
| 2021 | ICML | Robust Policy Gradient against Strong Data Corruption. | Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun |
| 2020 | AAAI | Optimal Attack against Autoregressive Models by Manipulating the Environment. | Yiding Chen, Xiaojin Zhu |