Decentralized Multi-player Multi-armed Bandits with No Collision Information. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (AISTATS, 2020)

PMGT-VR: A decentralized proximal-gradient algorithmic framework with variance reduction. - Haishan Ye; Wei Xiong 015; Tong Zhang 001 (CoRR, 2020)

Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (NeurIPS, 2021)

(Almost) Free Incentivized Exploration from Decentralized Learning Agents. - Chengshuai Shi; Haifeng Xu; Wei Xiong 015; Cong Shen 001 (NeurIPS, 2021)

Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. - Pushi Zhang; Xiaoyu Chen; Li Zhao 007; Wei Xiong 015; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2021)

A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. - Wei Xiong 015; Han Zhong 001; Chengshuai Shi; Cong Shen 001; Tong Zhang 001 (ICML, 2022)

Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. - Han Zhong 001; Wei Xiong 015; Jiyuan Tan; Liwei Wang 001; Tong Zhang 001; Zhaoran Wang 001; Zhuoran Yang (ICML, 2022)

GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. - Han Zhong 001; Wei Xiong 015; Sirui Zheng; Liwei Wang 001; Zhaoran Wang 001; Zhuoran Yang; Tong Zhang 001 (CoRR, 2022)

Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. - Wei Xiong 015; Han Zhong 001; Chengshuai Shi; Cong Shen 001; Liwei Wang 001; Tong Zhang 001 (ICLR, 2023)

Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (ICML, 2023)

Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. - Chenlu Ye; Wei Xiong 015; Quanquan Gu; Tong Zhang 001 (ICML, 2023)

Reward Teaching for Federated Multi-armed Bandits. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (ISIT, 2023)

Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration. - Zhihan Liu; Miao Lu; Wei Xiong 015; Han Zhong 001; Hao Hu; Shenao Zhang; Sirui Zheng; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2023)

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. - Hanze Dong; Wei Xiong 015; Deepanshu Goyal; Rui Pan 002; Shizhe Diao; Jipeng Zhang; Kashun Shum; Tong Zhang 001 (CoRR, 2023)

One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration. - Zhihan Liu; Miao Lu; Wei Xiong 015; Han Zhong 001; Hao Hu; Shenao Zhang; Sirui Zheng; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2023)

Mitigating the Alignment Tax of RLHF. - Yong Lin; Hangyu Lin; Wei Xiong 015; Shizhe Diao; Jianmeng Liu; Jipeng Zhang; Rui Pan 002; Haoxiang Wang 003; Wenbin Hu 002; Hanning Zhang; Hanze Dong; Renjie Pi; et al. (CoRR, 2023)

Gibbs Sampling from Human Feedback: A Provable KL- constrained Framework for RLHF. - Wei Xiong 015; Hanze Dong; Chenlu Ye; Han Zhong 001; Nan Jiang 008; Tong Zhang 001 (CoRR, 2023)

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. - Hanze Dong; Wei Xiong 015; Deepanshu Goyal; Yihan Zhang; Winnie Chow; Rui Pan 002; Shizhe Diao; Jipeng Zhang; Kashun Shum; Tong Zhang 001 (Trans. Mach. Learn. Res., 2023)

Reward Teaching for Federated Multiarmed Bandits. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (IEEE Trans. Signal Process., 2023)

Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. - Haoxiang Wang 003; Yong Lin; Wei Xiong 015; Rui Yang 010; Shizhe Diao; Shuang Qiu; Han Zhao 002; Tong Zhang 001 (ACL (1), 2024)

Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization. - Renjie Pi; Tianyang Han; Wei Xiong 015; Jipeng Zhang; Runtao Liu; Rui Pan 002; Tong Zhang 001 (ECCV (33), 2024)

Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. - Haoxiang Wang 003; Wei Xiong 015; Tengyang Xie; Han Zhao 002; Tong Zhang 001 (EMNLP (Findings), 2024)

Mitigating the Alignment Tax of RLHF. - Yong Lin; Hangyu Lin; Wei Xiong 015; Shizhe Diao; Jianmeng Liu; Jipeng Zhang; Rui Pan 002; Haoxiang Wang 003; Wenbin Hu 002; Hanning Zhang; Hanze Dong; Renjie Pi; et al. (EMNLP, 2024)

Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint. - Wei Xiong 015; Hanze Dong; Chenlu Ye; Ziqi Wang 003; Han Zhong 001; Heng Ji 001; Nan Jiang 008; Tong Zhang 001 (ICML, 2024)

LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. - Shizhe Diao; Rui Pan 002; Hanze Dong; Kashun Shum; Jipeng Zhang; Wei Xiong 015; Tong Zhang 001 (NAACL (Demonstrations), 2024)

Online Iterative Reinforcement Learning from Human Feedback with General Preference Model. - Chenlu Ye; Wei Xiong 015; Yuheng Zhang; Hanze Dong; Nan Jiang 008; Tong Zhang 001 (NeurIPS, 2024)

A Theoretical Analysis of Nash Learning from Human Feedback under General KL-Regularized Preference. - Chenlu Ye; Wei Xiong 015; Yuheng Zhang; Nan Jiang 008; Tong Zhang 001 (CoRR, 2024)

DPO Meets PPO: Reinforced Token Optimization for RLHF. - Han Zhong 001; Guhao Feng; Wei Xiong 015; Li Zhao 007; Di He 001; Jiang Bian 002; Liwei Wang 001 (CoRR, 2024)

RRM: Robust Reward Model Training Mitigates Reward Hacking. - Tianqi Liu 002; Wei Xiong 015; Jie Ren 006; Lichang Chen; Junru Wu; Rishabh Joshi; Yang Gao; Jiaming Shen; Zhen Qin 001; Tianhe Yu; Daniel Sohn; Anastasiia Makarova; et al. (CoRR, 2024)

RLHF Workflow: From Reward Modeling to Online RLHF. - Hanze Dong; Wei Xiong 015; Bo Pang 004; Haoxiang Wang 003; Han Zhao 002; Yingbo Zhou; Nan Jiang 008; Doyen Sahoo; Caiming Xiong; Tong Zhang 001 (Trans. Mach. Learn. Res., 2024)

From Lists to Emojis: How Format Bias Affects Model Alignment. - Xuanchang Zhang; Wei Xiong 015; Lichang Chen; Tianyi Zhou 001; Heng Huang; Tong Zhang 001 (ACL (1), 2025)

RRM: Robust Reward Model Training Mitigates Reward Hacking. - Tianqi Liu 002; Wei Xiong 015; Jie Ren 006; Lichang Chen; Junru Wu; Rishabh Joshi; Yang Gao; Jiaming Shen; Zhen Qin 001; Tianhe Yu; Daniel Sohn; Anastasia Makarova; et al. (ICLR, 2025)

Building Math Agents with Multi-Turn Iterative Preference Learning. - Wei Xiong 015; Chengshuai Shi; Jiaming Shen; Aviv Rosenberg 002; Zhen Qin 001; Daniele Calandriello; Misha Khalman; Rishabh Joshi; Bilal Piot; Mohammad Saleh; Chi Jin; Tong Zhang 001; et al. (ICLR, 2025)

LLM Alignment as Retriever Optimization: An Information Retrieval Perspective. - Bowen Jin; Jinsung Yoon; Zhen Qin 001; Ziqi Wang 003; Wei Xiong 015; Yu Meng 001; Jiawei Han 001; Sercan Ö. Arik (CoRR, 2025)

Logarithmic Regret for Online KL-Regularized Reinforcement Learning. - Heyang Zhao; Chenlu Ye; Wei Xiong 015; Quanquan Gu; Tong Zhang 001 (CoRR, 2025)

Self-rewarding correction for mathematical reasoning. - Wei Xiong 015; Hanning Zhang; Chenlu Ye; Lichang Chen; Nan Jiang 008; Tong Zhang 001 (CoRR, 2025)

A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce. - Wei Xiong 015; Jiarui Yao; Yuhui Xu; Bo Pang 004; Lei Wang 185; Doyen Sahoo; Junnan Li 001; Nan Jiang 008; Tong Zhang 001; Caiming Xiong; Hanze Dong (CoRR, 2025)

Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL. - Jiarui Yao; Yifan Hao 002; Hanning Zhang; Hanze Dong; Wei Xiong 015; Nan Jiang 008; Tong Zhang 001 (CoRR, 2025)