| Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates Y Liu, H Guo International Conference on Machine Learning, 2020 | 279 | 2020 |
| Reason for future, act for now: A principled framework for autonomous llm agents with provable sample efficiency Z Liu, H Hu, S Zhang, H Guo, S Ke, B Liu, Z Wang arXiv preprint arXiv:2309.17382, 2023 | 45* | 2023 |
| Provably mitigating overoptimization in rlhf: Your sft loss is implicitly an adversarial regularizer Z Liu, M Lu, S Zhang, B Liu, H Guo, Y Yang, J Blanchet, Z Wang arXiv preprint arXiv:2405.16436, 2024 | 34 | 2024 |
| Human-instruction-free llm self-alignment with limited samples H Guo, Y Yao, W Shen, J Wei, X Zhang, Z Wang, Y Liu arXiv preprint arXiv:2401.06785, 2024 | 18 | 2024 |
| Provably efficient offline reinforcement learning for partially observable markov decision processes H Guo, Q Cai, Y Zhang, Z Yang, Z Wang International Conference on Machine Learning (Spotlight), 8016-8038, 2022 | 18 | 2022 |
| Behavior Contrastive Learning for Unsupervised Skill Discovery R Yang, C Bai, H Guo, S Li, B Zhao, Z Wang, P Liu, X Li International Conference on Machine Learning, 2023 | 17 | 2023 |
| Measuring and Reducing LLM Hallucination without Gold-Standard Answers J Wei, Y Yao, JF Ton, H Guo, A Estornell, Y Liu arXiv preprint arXiv:2402.10412, 2024 | 16 | 2024 |
| Policy learning using weak supervision J Wang*, H Guo*, Z Zhu*, Y Liu Advances in Neural Information Processing Systems 34, 19960-19973, 2021 | 13 | 2021 |
| Decentralized single-timescale actor-critic on zero-sum two-player stochastic games H Guo, Z Fu, Z Yang, Z Wang International Conference on Machine Learning (Spotlight), 3899-3909, 2021 | 11 | 2021 |
| Improving reinforcement learning from human feedback using contrastive rewards W Shen, X Zhang, Y Yao, R Zheng, H Guo, Y Liu arXiv preprint arXiv:2403.07708, 2024 | 8 | 2024 |
| Can large language models play games? a case study of a self-play approach H Guo, Z Liu, Y Zhang, Z Wang arXiv preprint arXiv:2403.05632, 2024 | 8 | 2024 |
| Signal instructed coordination in cooperative multi-agent reinforcement learning L Chen, H Guo, Y Du, F Fang, H Zhang, W Zhang, Y Yu Distributed Artificial Intelligence: Third International Conference, DAI …, 2022 | 6 | 2022 |
| Toward Optimal LLM Alignments Using Two-Player Games R Zheng*, H Guo*, Z Liu*, X Zhang*, Y Yao, X Xu, Z Wang, Z Xi, T Gui, ... arXiv preprint arXiv:2406.10977, 2024 | 2 | 2024 |
| BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning H Zhong, Y Yin, S Zhang, X Xu, Y Liu, Y Zuo, Z Liu, B Liu, S Zheng, H Guo, ... arXiv preprint arXiv:2501.18858, 2025 | | 2025 |
| Machine learning model alignment Y Yao, H Guo, X Zhang, Y Liu US Patent App. 18/900,432, 2025 | | 2025 |
| Machine learning model evaluation Y Yao, J Wei, TON Jean-Francois, H Guo, A Estornell, Y Liu US Patent App. 18/885,135, 2025 | | 2025 |
| Diverse randomized value functions: A provably pessimistic approach for offline reinforcement learning X Yu, C Bai, H Guo, C Wang, Z Wang Information Sciences 680, 121146, 2024 | | 2024 |
| Progressive LLM Alignments Using Two-Player Games R Zheng, H Guo, Z Liu, X Zhang, Y Yao, X Xu, Z Wang, Z Xi, T Gui, ... | | |
| Robust RLHF with Noisy Rewards W Shen, X Zhang, Y Yao, R Zheng, H Guo, Y Liu | | |
| Lightweight Uncertainty for Offline Reinforcement Learning via Bayesian Posterior X Yu, C Bai, H Guo, L Wang, C Wang, Z Wang | | |
Yang LiuComputer Science and Engineering, UC Santa CruzVahvistettu sähköpostiosoite verkkotunnuksessa ucsc.edu