Wei Xiong - RankMe

60 papers A* 17A 1B 1Journal 36Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PMGT-VR: A Decentralized Proximal-Gradient Algorithmic Framework With Variance Reduction. IEEE Trans. Pattern Anal. Mach. Intell. Haishan Ye, Wei Xiong, Tong Zhang
2025	J	`jnl`	A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce. CoRR Wei Xiong, Jiarui Yao, Yuhui Xu, Bo Pang, Lei Wang, Doyen Sahoo, Junnan Li, Nan Jiang, Tong Zhang, Caiming Xiong, Hanze Dong
2025	A*	`conf`	Building Math Agents with Multi-Turn Iterative Preference Learning. ICLR Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu
2025	A*	`conf`	DPO Meets PPO: Reinforced Token Optimization for RLHF. ICML Han Zhong, Zikang Shan, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang
2025	—	`conf`	From Lists to Emojis: How Format Bias Affects Model Alignment. ACL (1) Xuanchang Zhang, Wei Xiong, Lichang Chen, Tianyi Zhou, Heng Huang, Tong Zhang
2025	A*	`conf`	LLM Alignment as Retriever Optimization: An Information Retrieval Perspective. ICML Bowen Jin, Jinsung Yoon, Zhen Qin, Ziqi Wang, Wei Xiong, Yu Meng, Jiawei Han, Sercan Ö. Arik
2025	J	`jnl`	LLM Alignment as Retriever Optimization: An Information Retrieval Perspective. CoRR Bowen Jin, Jinsung Yoon, Zhen Qin, Ziqi Wang, Wei Xiong, Yu Meng, Jiawei Han, Sercan Ö. Arik
2025	A*	`conf`	Logarithmic Regret for Online KL-Regularized Reinforcement Learning. ICML Heyang Zhao, Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2025	J	`jnl`	Logarithmic Regret for Online KL-Regularized Reinforcement Learning. CoRR Heyang Zhao, Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2025	J	`jnl`	Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL. CoRR Jiarui Yao, Yifan Hao, Hanning Zhang, Hanze Dong, Wei Xiong, Nan Jiang, Tong Zhang
2025	A*	`conf`	RRM: Robust Reward Model Training Mitigates Reward Hacking. ICLR Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasia Makarova, Jeremiah Zhe Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
2025	J	`jnl`	Reinforce-Ada: An Adaptive Sampling Framework for Reinforce-Style LLM Training. CoRR Wei Xiong, Chenlu Ye, Baohao Liao, Hanze Dong, Xinxing Xu, Christof Monz, Jiang Bian, Nan Jiang, Tong Zhang
2025	J	`jnl`	Self-rewarding correction for mathematical reasoning. CoRR Wei Xiong, Hanning Zhang, Chenlu Ye, Lichang Chen, Nan Jiang, Tong Zhang
2024	J	`jnl`	A Theoretical Analysis of Nash Learning from Human Feedback under General KL-Regularized Preference. CoRR Chenlu Ye, Wei Xiong, Yuheng Zhang, Nan Jiang, Tong Zhang
2024	—	`conf`	Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. ACL (1) Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
2024	J	`jnl`	Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. CoRR Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
2024	J	`jnl`	Building Math Agents with Multi-Turn Iterative Preference Learning. CoRR Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu
2024	J	`jnl`	DPO Meets PPO: Reinforced Token Optimization for RLHF. CoRR Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang
2024	J	`jnl`	From Lists to Emojis: How Format Bias Affects Model Alignment. CoRR Xuanchang Zhang, Wei Xiong, Lichang Chen, Tianyi Zhou, Heng Huang, Tong Zhang
2024	—	`conf`	Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. EMNLP (Findings) Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024	J	`jnl`	Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. CoRR Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024	A*	`conf`	Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint. ICML Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, Tong Zhang
2024	—	`conf`	LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. NAACL (Demonstrations) Shizhe Diao, Rui Pan, Hanze Dong, Kashun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang
2024	A*	`conf`	Mitigating the Alignment Tax of RLHF. EMNLP Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan Yao, Tong Zhang
2024	A*	`conf`	Online Iterative Reinforcement Learning from Human Feedback with General Preference Model. NeurIPS Chenlu Ye, Wei Xiong, Yuheng Zhang, Hanze Dong, Nan Jiang, Tong Zhang
2024	J	`jnl`	RLHF Workflow: From Reward Modeling to Online RLHF. CoRR Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
2024	J	`jnl`	RLHF Workflow: From Reward Modeling to Online RLHF. Trans. Mach. Learn. Res. Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
2024	J	`jnl`	RRM: Robust Reward Model Training Mitigates Reward Hacking. CoRR Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasiia Makarova, Jeremiah Z. Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
2024	—	`conf`	Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization. ECCV (33) Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, Tong Zhang
2024	J	`jnl`	Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization. CoRR Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, Tong Zhang
2023	A*	`conf`	Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. ICML Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2023	J	`jnl`	Gibbs Sampling from Human Feedback: A Provable KL- constrained Framework for RLHF. CoRR Wei Xiong, Hanze Dong, Chenlu Ye, Han Zhong, Nan Jiang, Tong Zhang
2023	J	`jnl`	LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. CoRR Shizhe Diao, Rui Pan, Hanze Dong, Kashun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang
2023	A*	`conf`	Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration. NeurIPS Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang
2023	J	`jnl`	Mitigating the Alignment Tax of RLHF. CoRR Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Yuan Yao, Tong Zhang
2023	A*	`conf`	Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. ICLR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
2023	J	`jnl`	One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration. CoRR Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang
2023	A*	`conf`	Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources. ICML Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2023	J	`jnl`	Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources. CoRR Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2023	J	`jnl`	RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. CoRR Hanze Dong, Wei Xiong, Deepanshu Goyal, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang
2023	J	`jnl`	RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. Trans. Mach. Learn. Res. Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang
2023	B	`conf`	Reward Teaching for Federated Multi-armed Bandits. ISIT Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2023	J	`jnl`	Reward Teaching for Federated Multi-armed Bandits. CoRR Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2023	J	`jnl`	Reward Teaching for Federated Multiarmed Bandits. IEEE Trans. Signal Process. Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2022	A*	`conf`	A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. ICML Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang
2022	J	`jnl`	A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. CoRR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang
2022	J	`jnl`	Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. CoRR Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2022	J	`jnl`	GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. CoRR Han Zhong, Wei Xiong, Sirui Zheng, Liwei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang
2022	J	`jnl`	Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. CoRR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
2022	A*	`conf`	Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. ICML Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
2022	J	`jnl`	Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. CoRR Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
2021	A*	`conf`	(Almost) Free Incentivized Exploration from Decentralized Learning Agents. NeurIPS Chengshuai Shi, Haifeng Xu, Wei Xiong, Cong Shen
2021	J	`jnl`	(Almost) Free Incentivized Exploration from Decentralized Learning Agents. CoRR Chengshuai Shi, Haifeng Xu, Wei Xiong, Cong Shen
2021	A*	`conf`	Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. NeurIPS Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
2021	J	`jnl`	Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. CoRR Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
2021	A*	`conf`	Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization. NeurIPS Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2021	J	`jnl`	Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization. CoRR Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2020	A	`conf`	Decentralized Multi-player Multi-armed Bandits with No Collision Information. AISTATS Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2020	J	`jnl`	Decentralized Multi-player Multi-armed Bandits with No Collision Information. CoRR Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang
2020	J	`jnl`	PMGT-VR: A decentralized proximal-gradient algorithmic framework with variance reduction. CoRR Haishan Ye, Wei Xiong, Tong Zhang