Ye, Haotian

17 publications

NeurIPS 2025 A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning Yuzheng Hu, Fan Wu, Haotian Ye, David Forsyth, James Zou, Nan Jiang, Jiaqi W. Ma, Han Zhao

ICCV 2025 CHORDS: Diffusion Sampling Accelerator with Multi-Core Hierarchical ODE Solvers Jiaqi Han, Haotian Ye, Puheng Li, Minkai Xu, James Zou, Stefano Ermon

AISTATS 2025 Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models Haotian Ye, Himanshu Jain, Chong You, Ananda Theertha Suresh, Haowei Lin, James Zou, Felix Yu

ICLR 2025 Reducing Hallucinations in Large Vision-Language Models via Latent Space Steering Sheng Liu, Haotian Ye, James Zou

ICLR 2025 TFG-Flow: Training-Free Guidance in Multimodal Generative Flow Haowei Lin, Shanda Li, Haotian Ye, Yiming Yang, Stefano Ermon, Yitao Liang, Jianzhu Ma

ICLRW 2024 DOF: Accelerating High-Order Differential Operators with Forward Propagation Ruichen Li, Chuwei Wang, Haotian Ye, Di He, Liwei Wang

NeurIPS 2024 Geometric Trajectory Diffusion Models Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon

ICML 2024 In-Context Vectors: Making in Context Learning More Effective and Controllable Through Latent Space Steering Sheng Liu, Haotian Ye, Lei Xing, James Y. Zou

ICML 2024 Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel Mcfarland, James Y. Zou

ICML 2024 Selecting Large Language Model to Fine-Tune via Rectified Scaling Law Haowei Lin, Baizhou Huang, Haotian Ye, Qinyu Chen, Zihao Wang, Sujian Li, Jianzhu Ma, Xiaojun Wan, James Zou, Yitao Liang

ICLRW 2024 Selecting Large Language Model to Fine-Tune via Rectified Scaling Law Haowei Lin, Baizhou Huang, Haotian Ye, Qinyu Chen, Zihao Wang, Sujian Li, Jianzhu Ma, Xiaojun Wan, James Zou, Yitao Liang

NeurIPS 2024 TFG: Unified Training-Free Guidance for Diffusion Models Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Zou, Stefano Ermon

ICLR 2023 Discovering Latent Knowledge in Language Models Without Supervision Collin Burns, Haotian Ye, Dan Klein, Jacob Steinhardt

AISTATS 2023 Freeze Then Train: Towards Provable Representation Learning Under Spurious Correlations and Feature Noise Haotian Ye, James Zou, Linjun Zhang

ICML 2023 On the Power of Pre-Training for Generalization in RL: Provable Benefits and Hardness Haotian Ye, Xiaoyu Chen, Liwei Wang, Simon Shaolei Du

NeurIPS 2023 Towards Revealing the Mystery Behind Chain of Thought: A Theoretical Perspective Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang

NeurIPS 2021 Towards a Theoretical Framework of Out-of-Distribution Generalization Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang