| Raft: Reward ranked finetuning for generative foundation model alignment ( α-β), H Dong*, W Xiong*, D Goyal, Z Yihan, C Winnie, R Pan, S Diao, ... TMLR (Invited Presentation @ ICLR 2025), 2023 | 648* | 2023 |
| Iterative preference learning from human feedback: Bridging theory and practice for rlhf under kl-constraint W Xiong*, H Dong*, C Ye*, Z Wang, H Zhong, H Ji, N Jiang, T Zhang ICML 2024, 2023 | 353* | 2023 |
| Interpretable preferences via multi-objective reward modeling and mixture-of-experts H Wang*, W Xiong*, T Xie, H Zhao, T Zhang ACL 2024, 2024 | 302 | 2024 |
| RLHF workflow: From reward modeling to online rlhf ( α-β), H Dong*, W Xiong*, B Pang*, H Wang*, H Zhao, Y Zhou, N Jiang, ... TMLR, 2024 | 297* | 2024 |
| Mitigating the alignment tax of rlhf ( α-β), Y Lin*, H Lin*, W Xiong*, S Diao*, J Liu, J Zhang, R Pan, H Wang, ... ACL 2024, 2023 | 225* | 2023 |
| Arithmetic control of llms for diverse user preferences: Directional preference alignment with multi-objective rewards H Wang*, Y Lin*, W Xiong*, R Yang, S Diao, S Qiu, H Zhao, T Zhang ACL 2024, 2024 | 137 | 2024 |
| Dpo meets ppo: Reinforced token optimization for rlhf H Zhong, Z Shan, G Feng, W Xiong, X Cheng, L Zhao, D He, J Bian, ... ICML 2025, 2024 | 99 | 2024 |
| A theoretical analysis of nash learning from human feedback under general kl-regularized preference ( α-β), C Ye*, W Xiong*, Y Zhang*, N Jiang, T Zhang NeurIPS 2024, 2024 | 86* | 2024 |
| A posterior sampling framework for interactive decision making ( α-β), H Zhong*, W Xiong*, S Zheng, L Wang, Z Wang, Z Yang, T Zhang Mathematics of Operations Research (MOR), 2022 | 83* | 2022 |
| A minimalist approach to llm reasoning: from rejection sampling to reinforce W Xiong, J Yao, Y Xu, B Pang, L Wang, D Sahoo, J Li, N Jiang, T Zhang, ... Technical Report, 2025 | 78 | 2025 |
| Strengthening multimodal large language model with bootstrapped preference optimization R Pi, T Han, W Xiong, J Zhang, R Liu, R Pan, T Zhang ECCV 2024, 382-398, 2024 | 77 | 2024 |
| Lmflow: An extensible toolkit for finetuning and inference of large foundation models S Diao, R Pan, H Dong, KS Shum, J Zhang, W Xiong, T Zhang NAACL 2024, best paper award in demo paper track, 2023 | 75 | 2023 |
| Building math agents with multi-turn iterative preference learning W Xiong, C Shi, J Shen, A Rosenberg, Z Qin, D Calandriello, M Khalman, ... ICLR 2025, 2024 | 61 | 2024 |
| Nearly minimax optimal offline reinforcement learning with linear function approximation: Single-agent mdp and markov game W Xiong, H Zhong, C Shi, C Shen, L Wang, T Zhang ICLR 2023, 2022 | 60 | 2022 |
| Pessimistic minimax value iteration: Provably efficient equilibrium learning from offline datasets H Zhong, W Xiong, J Tan, L Wang, T Zhang, Z Wang, Z Yang ICML 2022, 2022 | 59 | 2022 |
| Maximize to explore: One objective function fusing estimation, planning, and exploration Z Liu, M Lu, W Xiong, H Zhong, H Hu, S Zhang, S Zheng, Z Yang, Z Wang NeurIPS 2024, 2024 | 51* | 2024 |
| Decentralized multi-player multi-armed bandits with no collision information C Shi, W Xiong, C Shen, J Yang AISTATS 2020, 2020 | 45 | 2020 |
| Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes C Ye, W Xiong, Q Gu, T Zhang ICML 2023, 2022 | 42 | 2022 |
| Self-rewarding correction for mathematical reasoning W Xiong, H Zhang, C Ye, L Chen, N Jiang, T Zhang arXiv preprint arXiv:2502.19613, 2025 | 41 | 2025 |
| Rrm: Robust reward model training mitigates reward hacking T Liu, W Xiong, J Ren, L Chen, J Wu, R Joshi, Y Gao, J Shen, Z Qin, T Yu, ... ICLR 2025, 2024 | 41 | 2024 |
Tong ZhangUIUCVerified email at tongzhang-ml.org
