Vehicle Trajectory Prediction Using Intention-based Conditional Variational Autoencoder. - Xidong Feng; Zhepeng Cen; Jianming Hu; Yi Zhang 029 (ITSC, 2019)

Will this Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora. - Hancheng Cao; Mengjie Cheng; Zhepeng Cen; Daniel A. McFarland; Xiang Ren 001 (EMNLP (Findings), 2020)

Constrained Variational Policy Optimization for Safe Reinforcement Learning. - Zuxin Liu; Zhepeng Cen; Vladislav Isenbaev; Wei Liu; Zhiwei Steven Wu; Bo Li 026; Ding Zhao (ICML, 2022)

Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS). - Mansur Arief; Zhepeng Cen; Zhenyuan Liu; Zhiyuan Huang; Bo Li 026; Henry Lam; Ding Zhao (ITSC, 2022)

Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling. - Mansur Arief; Zhepeng Cen; Zhenyuan Liu; Zhiyuan Huang; Henry Lam; Bo Li 026; Ding Zhao (CoRR, 2022)

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. - Mengdi Xu; Zuxin Liu; Peide Huang; Wenhao Ding; Zhepeng Cen; Bo Li 026; Ding Zhao (CoRR, 2022)

On the Robustness of Safe Reinforcement Learning under Observational Perturbations. - Zuxin Liu; Zijian Guo 002; Zhepeng Cen; Huan Zhang 001; Jie Tan 001; Bo Li 026; Ding Zhao (ICLR, 2023)

Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data. - Zuxin Liu; Zijian Guo 002; Zhepeng Cen; Huan Zhang 001; Yihang Yao; Hanjiang Hu; Ding Zhao (ICML, 2023)

Constrained Decision Transformer for Offline Safe Reinforcement Learning. - Zuxin Liu; Zijian Guo 002; Yihang Yao; Zhepeng Cen; Wenhao Yu 003; Tingnan Zhang; Ding Zhao (ICML, 2023)

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. - Yihang Yao; Zuxin Liu; Zhepeng Cen; Jiacheng Zhu; Wenhao Yu 003; Tingnan Zhang; Ding Zhao (NeurIPS, 2023)

Datasets and Benchmarks for Offline Safe Reinforcement Learning. - Zuxin Liu; Zijian Guo 002; Haohong Lin; Yihang Yao; Jiacheng Zhu; Zhepeng Cen; Hanjiang Hu; Wenhao Yu 003; Tingnan Zhang; Jie Tan 001; Ding Zhao (CoRR, 2023)

Learning from Sparse Offline Datasets via Conservative Density Estimation. - Zhepeng Cen; Zuxin Liu; Zitong Wang 005; Yihang Yao; Henry Lam; Ding Zhao (ICLR, 2024)

Feasibility Consistent Representation Learning for Safe Reinforcement Learning. - Zhepeng Cen; Yihang Yao; Zuxin Liu; Ding Zhao (ICML, 2024)

Gradient shaping for multi-constraint safe reinforcement learning. - Yihang Yao; Zuxin Liu; Zhepeng Cen; Peide Huang; Tingnan Zhang; Wenhao Yu 003; Ding Zhao (L4DC, 2024)

OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning. - Yihang Yao; Zhepeng Cen; Wenhao Ding; Haohong Lin; Shiqi Liu 005; Tingnan Zhang; Wenhao Yu 003; Ding Zhao (NeurIPS, 2024)

Your Language Model May Think Too Rigidly: Achieving Reasoning Consistency with Symmetry-Enhanced Training. - Yihang Yao; Zhepeng Cen; Miao Li; William Han; Yuyou Zhang; Emerson Liu; Zuxin Liu; Chuang Gan 001; Ding Zhao (ACL (Findings), 2025)

Safety is Not Only About Refusal: Reasoning-Enhanced Fine-tuning for Interpretable LLM Safety. - Yuyou Zhang; Miao Li; William Han; Yihang Yao; Zhepeng Cen; Ding Zhao (ACL (Findings), 2025)

Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. - Zhepeng Cen; Yao Liu 009; Siliang Zeng; Pratik Chaudhari; Huzefa Rangwala; George Karypis; Rasool Fakoor (Trans. Mach. Learn. Res., 2025)

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework. - William Han; Chaojing Duan; Zhepeng Cen; Yihang Yao; Xiaoyu Song; Atharva Mhaskar; Dylan Leong; Michael A. Rosenberg; Emerson Liu; Ding Zhao (CoRR, 2025)

Behavior Injection: Preparing Language Models for Reinforcement Learning. - Zhepeng Cen; Yihang Yao; William Han; Zuxin Liu; Ding Zhao (CoRR, 2025)