Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot. - Jingtong Su; Yihang Chen; Tianle Cai; Tianhao Wu 002; Ruiqi Gao; Liwei Wang 001; Jason D. Lee (NeurIPS, 2020)

On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP. - Tianhao Wu 002; Yunchang Yang; Simon S. Du; Liwei Wang 001 (ICML, 2021)

A Unified Framework for Conservative Exploration. - Yunchang Yang; Tianhao Wu 002; Han Zhong 001; Evrard Garcelon; Matteo Pirotta; Alessandro Lazaric; Liwei Wang 001; Simon S. Du (CoRR, 2021)

A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. - Yunchang Yang; Tianhao Wu 002; Han Zhong 001; Evrard Garcelon; Matteo Pirotta; Alessandro Lazaric; Liwei Wang 001; Simon Shaolei Du (ICLR, 2022)

Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. - Tianhao Wu 002; Yunchang Yang; Han Zhong 001; Liwei Wang 001; Simon S. Du; Jiantao Jiao (ICML, 2022)

Statistical Inference on Multi-armed Bandits with Delayed Feedback. - Lei Shi; Jingshen Wang; Tianhao Wu 002 (ICML, 2023)

A Reduction-based Framework for Sequential Decision Making with Delayed Feedback. - Yunchang Yang; Han Zhong 001; Tianhao Wu 002; Bin Liu; Liwei Wang 001; Simon S. Du (NeurIPS, 2023)

Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment. - Tianhao Wu 002; Banghua Zhu; Ruoyu Zhang; Zhaojin Wen; Kannan Ramchandran; Jiantao Jiao (CoRR, 2023)

From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline. - Tianle Li; Wei-Lin Chiang; Evan Frick; Lisa Dunlap; Tianhao Wu 002; Banghua Zhu; Joseph E. Gonzalez; Ion Stoica (CoRR, 2024)

RouteLLM: Learning to Route LLMs with Preference Data. - Isaac Ong; Amjad Almahairi; Vincent Wu; Wei-Lin Chiang; Tianhao Wu 002; Joseph E. Gonzalez; M. Waleed Kadous; Ion Stoica (CoRR, 2024)

Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge. - Tianhao Wu 002; Weizhe Yuan; Olga Golovneva; Jing Xu; Yuandong Tian; Jiantao Jiao; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

Thinking LLMs: General Instruction Following with Thought Generation. - Tianhao Wu 002; Janice Lan; Weizhe Yuan; Jiantao Jiao; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

RouteLLM: Learning to Route LLMs from Preference Data. - Isaac Ong; Amjad Almahairi; Vincent Wu; Wei-Lin Chiang; Tianhao Wu 002; Joseph E. Gonzalez; M. Waleed Kadous; Ion Stoica (ICLR, 2025)

EmbedLLM: Learning Compact Representations of Large Language Models. - Richard Zhuang; Tianhao Wu 002; Zhaojin Wen; Andrew Li; Jiantao Jiao; Kannan Ramchandran (ICLR, 2025)

Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback. - Yen-Ting Lin; Di Jin; Tengyu Xu; Tianhao Wu 002; Sainbayar Sukhbaatar; Chen Zhu; Yun He; Yun-Nung Chen; Jason Weston; Yuandong Tian; Arash Rahnama; Sinong Wang; et al. (CoRR, 2025)

R.I.P.: Better Models by Survival of the Fittest Prompts. - Ping Yu; Weizhe Yuan; Olga Golovneva; Tianhao Wu 002; Sainbayar Sukhbaatar; Jason Weston; Jing Xu (CoRR, 2025)

Sample Complexity and Representation Ability of Test-time Scaling Paradigms. - Baihe Huang; Shanda Li; Tianhao Wu 002; Yiming Yang; Ameet Talwalkar; Kannan Ramchandran; Michael I. Jordan; Jiantao Jiao (CoRR, 2025)