Chen, Haoxian

10 publications

ICLR 2026 TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning Tunyu Zhang, Haizhou Shi, Yibin Wang, Hengyi Wang, Xiaoxiao He, Zhuowei Li, Haoxian Chen, Ligong Han, Kai Xu, Huan Zhang, Dimitris N. Metaxas, Hao Wang

ICLR 2025 MallowsPO: Fine-Tune Your LLM with Preference Dispersions Haoxian Chen, Hanyang Zhao, Henry Lam, David Yao, Wenpin Tang

ICML 2025 Score as Action: Fine Tuning Diffusion Generative Models by Continuous-Time Reinforcement Learning Hanyang Zhao, Haoxian Chen, Ji Zhang, David Yao, Wenpin Tang

ICLRW 2025 Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-Time Reinforcement Learning Hanyang Zhao, Haoxian Chen, Ji Zhang, David Yao, Wenpin Tang

NeurIPSW 2024 Mallows-DPO: Fine-Tune Your LLM with Preference Dispersions Haoxian Chen, Hanyang Zhao, Henry Lam, David Yao, Wenpin Tang

ICML 2022 From Block-Toeplitz Matrices to Differential Equations on Graphs: Towards a General Theory for Scalable Masked Transformers Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamas Sarlos, Adrian Weller, Thomas Weingarten

ICLR 2022 Hybrid Random Features Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael S Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller

AISTATS 2021 Learning Prediction Intervals for Regression: Generalization and Calibration Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang

ACML 2020 Constrained Reinforcement Learning via Policy Splitting Haoxian Chen, Henry Lam, Fengpei Li, Amirhossein Meisami

NeurIPS 2020 Demystifying Orthogonal Monte Carlo and Beyond Han Lin, Haoxian Chen, Krzysztof M Choromanski, Tianyi Zhang, Clement Laroche