Zhong, Han

37 publications

ICML 2025 BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning Han Zhong, Yutong Yin, Shenao Zhang, Xiaojun Xu, Yuanxin Liu, Yifei Zuo, Zhihan Liu, Boyi Liu, Sirui Zheng, Hongyi Guo, Liwei Wang, Mingyi Hong, Zhaoran Wang

ICML 2025 DPO Meets PPO: Reinforced Token Optimization for RLHF Han Zhong, Zikang Shan, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang

NeurIPS 2025 Less Is More: Improving LLM Alignment via Preference Data Selection Xun Deng, Han Zhong, Rui Ai, Fuli Feng, Zheng Wang, Xiangnan He

TMLR 2025 Self-Exploring Language Models: Active Preference Elicitation for Online Alignment Shenao Zhang, Donghan Yu, Hiteshi Sharma, Han Zhong, Zhihan Liu, Ziyi Yang, Shuohang Wang, Hany Hassan Awadalla, Zhaoran Wang

ICML 2025 The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability Jiachen Hu, Rui Ai, Han Zhong, Xiaoyu Chen, Liwei Wang, Zhaoran Wang, Zhuoran Yang

ICML 2024 A3S: A General Active Clustering Method with Pairwise Constraints Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang

ICML 2024 Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, John C.S. Lui, Wei Chen

ICMLW 2024 DPO Meets PPO: Reinforced Token Optimization for RLHF Han Zhong, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang

ICMLW 2024 Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm Miao Lu, Han Zhong, Tong Zhang, Jose Blanchet

NeurIPS 2024 Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms Miao Lu, Han Zhong, Tong Zhang, Jose Blanchet

AISTATS 2024 Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang

ICML 2024 Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF Under KL-Constraint Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, Tong Zhang

ICML 2024 Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret Han Zhong, Jiachen Hu, Yecheng Xue, Tongyang Li, Liwei Wang

NeurIPS 2024 Rethinking Model-Based, Policy-Based, and Value-Based Reinforcement Learning via the Lens of Representation Complexity Guhao Feng, Han Zhong

ICMLW 2024 Rethinking Model-Based, Policy-Based, and Value-Based Reinforcement Learning via the Lens of Representation Complexity Guhao Feng, Han Zhong

ICML 2024 Rewards-in-Context: Multi-Objective Alignment of Foundation Models with Dynamic Preference Adjustment Rui Yang, Xiaoman Pan, Feng Luo, Shuang Qiu, Han Zhong, Dong Yu, Jianshu Chen

ICLR 2024 Sample-Efficient Learning of Infinite-Horizon Average-Reward MDPs with General Function Approximation Jianliang He, Han Zhong, Zhuoran Yang

ICLR 2024 Towards Robust Offline Reinforcement Learning Under Diverse Data Corruption Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang

NeurIPS 2023 A Reduction-Based Framework for Sequential Decision Making with Delayed Feedback Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang, Simon S Du

NeurIPS 2023 A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong, Tong Zhang

JMLR 2023 Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan

NeurIPS 2023 Double Pessimism Is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage Jose Blanchet, Miao Lu, Tong Zhang, Han Zhong

NeurIPS 2023 Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang

ICLR 2023 Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang

NeurIPS 2023 Posterior Sampling for Competitive RL: Function Approximation and Partial Observation Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang

ICLR 2023 Provable Sim-to-Real Transfer in Continuous Domain with Partial Observations Jiachen Hu, Han Zhong, Chi Jin, Liwei Wang

NeurIPS 2023 Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang

ICLR 2022 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

ICML 2022 A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

ICLRW 2022 A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

ICLRW 2022 Can Reinforcement Learning Efficiently Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers？ Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael Jordan

ICML 2022 Human-in-the-Loop: Provably Efficient Preference-Based Reinforcement Learning with General Function Approximation Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang

ICML 2022 Nearly Optimal Policy Optimization with Stable at Any Time Guarantee Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon Du, Jiantao Jiao

ICML 2022 Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang

ICLRW 2022 Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang

NeurIPS 2022 Why Robust Generalization in Deep Learning Is Difficult: Perspective of Expressive Power Binghui Li, Jikai Jin, Han Zhong, John Hopcroft, Liwei Wang

NeurIPS 2021 Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs Han Zhong, Jiayi Huang, Lin Yang, Liwei Wang