| Starling-7b: Improving helpfulness and harmlessness with rlaif B Zhu, E Frick, T Wu, H Zhu, K Ganesan, WL Chiang, J Zhang, J Jiao First Conference on Language Modeling, 2024 | 113* | 2024 |
| Sanity-checking pruning methods: Random tickets can win the jackpot J Su, Y Chen, T Cai, T Wu, R Gao, L Wang, JD Lee Advances in neural information processing systems 33, 20390-20401, 2020 | 96 | 2020 |
| From crowdsourced data to high-quality benchmarks: Arena-hard and benchbuilder pipeline T Li, WL Chiang, E Frick, L Dunlap, T Wu, B Zhu, JE Gonzalez, I Stoica arXiv preprint arXiv:2406.11939, 2024 | 90 | 2024 |
| Pairwise proximal policy optimization: Language model alignment with comparative RL T Wu, B Zhu, R Zhang, Z Wen, K Ramchandran, J Jiao First Conference on Language Modeling, 2024 | 43* | 2024 |
| Meta-rewarding language models: Self-improving alignment with llm-as-a-meta-judge T Wu, W Yuan, O Golovneva, J Xu, Y Tian, J Jiao, J Weston, S Sukhbaatar arXiv preprint arXiv:2407.19594, 2024 | 42 | 2024 |
| RouteLLM: Learning to Route LLMs from Preference Data I Ong, A Almahairi, V Wu, WL Chiang, T Wu, JE Gonzalez, MW Kadous, ... The Thirteenth International Conference on Learning Representations, 2024 | 37 | 2024 |
| From generation to judgment: Opportunities and challenges of llm-as-a-judge D Li, B Jiang, L Huang, A Beigi, C Zhao, Z Tan, A Bhattacharjee, Y Jiang, ... arXiv preprint arXiv:2411.16594, 2024 | 25 | 2024 |
| On reinforcement learning with adversarial corruption and its application to block mdp T Wu, Y Yang, S Du, L Wang International Conference on Machine Learning, 11296-11306, 2021 | 19 | 2021 |
| Nearly optimal policy optimization with stable at any time guarantee T Wu, Y Yang, H Zhong, L Wang, S Du, J Jiao International Conference on Machine Learning, 24243-24265, 2022 | 15 | 2022 |
| A reduction-based framework for conservative bandits and reinforcement learning Y Yang, T Wu, H Zhong, E Garcelon, M Pirotta, A Lazaric, L Wang, SS Du arXiv preprint arXiv:2106.11692, 2021 | 9* | 2021 |
| Thinking llms: General instruction following with thought generation T Wu, J Lan, W Yuan, J Jiao, J Weston, S Sukhbaatar arXiv preprint arXiv:2410.10630, 2024 | 8 | 2024 |
| A reduction-based framework for sequential decision making with delayed feedback Y Yang, H Zhong, T Wu, B Liu, L Wang, SS Du Advances in Neural Information Processing Systems 36, 46362-46389, 2023 | 6 | 2023 |
| Statistical inference on multi-armed bandits with delayed feedback L Shi, J Wang, T Wu International Conference on Machine Learning, 31328-31352, 2023 | 5 | 2023 |
| DySpec: Faster Speculative Decoding with Dynamic Token Tree Structure Y Xiong, R Zhang, Y Li, T Wu, L Zou arXiv preprint arXiv:2410.11744, 2024 | 1 | 2024 |
| RIP: Better Models by Survival of the Fittest Prompts P Yu, W Yuan, O Golovneva, T Wu, S Sukhbaatar, J Weston, J Xu arXiv preprint arXiv:2501.18578, 2025 | | 2025 |
| Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback YT Lin, D Jin, T Xu, T Wu, S Sukhbaatar, C Zhu, Y He, YN Chen, J Weston, ... arXiv preprint arXiv:2501.10799, 2025 | | 2025 |
| EmbedLLM: Learning Compact Representations of Large Language Models R Zhuang, T Wu, Z Wen, A Li, J Jiao, K Ramchandran arXiv preprint arXiv:2410.02223, 2024 | | 2024 |
| Bench-O-Matic: Automating Benchmark Curation from Crowdsourced Data T Li, WL Chiang, E Frick, L Dunlap, T Wu, B Zhu, JE Gonzalez, I Stoica | | |
Jiantao JiaoAssistant Professor of EECS and Statistics, University of California, BerkeleyVahvistettu sähköpostiosoite verkkotunnuksessa berkeley.edu