Huang, Shengyi

8 publications

ICLR 2026 Tricks or Traps? a Deep Dive into RL for LLM Reasoning Zihe Liu, Jiashun Liu, Yancheng He, Weixun Wang, Jiaheng Liu, Ling Pan, Xinyu Hu, Shaopan Xiong, Ju Huang, Jian Hu, Shengyi Huang, Siran Yang, Jiamang Wang, Wenbo Su, Bo Zheng

ICLR 2025 Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron Courville

NeurIPS 2025 Generalizing Verifiable Instruction Following Valentina Pyatkin, Saumya Malik, Victoria Graf, Hamish Ivison, Shengyi Huang, Pradeep Dasigi, Nathan Lambert, Hannaneh Hajishirzi

ICLR 2024 Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform Shengyi Huang, Jiayi Weng, Rujikorn Charakorn, Min Lin, Zhongwen Xu, Santiago Ontanon

NeurIPSW 2024 Faster, More Efficient RLHF Through Off-Policy Asynchronous Learning Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron Courville

NeurIPS 2023 Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John Dickerson, Joseph Suarez

MLOSS 2022 CleanRL: High-Quality Single-File Implementations of Deep Reinforcement Learning Algorithms Shengyi Huang, Rousslan Fernand Julien Dossa, Chang Ye, Jeff Braga, Dipam Chakraborty, Kinal Mehta, João G.M. Araújo

NeurIPS 2022 EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine Jiayi Weng, Min Lin, Shengyi Huang, Bo Liu, Denys Makoviichuk, Viktor Makoviychuk, Zichen Liu, Yufan Song, Ting Luo, Yukun Jiang, Zhongwen Xu, Shuicheng Yan