Cen, Zhepeng

15 publications

NeurIPS 2025 Behavior Injection: Preparing Language Models for Reinforcement Learning Zhepeng Cen, Yihang Yao, William Han, Zuxin Liu, Ding Zhao

TMLR 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

ICLRW 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

DMLR 2024 Datasets and Benchmarks for Offline Safe Reinforcement Learning Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao

ICML 2024 Feasibility Consistent Representation Learning for Safe Reinforcement Learning Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao

L4DC 2024 Gradient Shaping for Multi-Constraint Safe Reinforcement Learning Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao

ICLR 2024 Learning from Sparse Offline Datasets via Conservative Density Estimation Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao

NeurIPS 2024 OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao

ICML 2023 Constrained Decision Transformer for Offline Safe Reinforcement Learning Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao

NeurIPS 2023 Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao

ICMLW 2023 Learning from Sparse Offline Datasets via Conservative Density Estimation Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao

ICLR 2023 On the Robustness of Safe Reinforcement Learning Under Observational Perturbations Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao

ICML 2023 Towards Robust and Safe Reinforcement Learning with Benign Off-Policy Data Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Yihang Yao, Hanjiang Hu, Ding Zhao

ICML 2022 Constrained Variational Policy Optimization for Safe Reinforcement Learning Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Steven Wu, Bo Li, Ding Zhao

NeurIPSW 2022 On the Robustness of Safe Reinforcement Learning Under Observational Perturbations Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao