Zhepeng Cen

According to our database, Zhepeng Cen authored at least 24 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization.

Yihang Yao, Zhepeng Cen, Haohong Lin, Shiqi Liu, Zuxin Liu, Jiacheng Zhu, Zhang-Wei Hong, Laixi Shi, Ding Zhao

CoRR, February, 2026

2025

LoCoBench-Agent: An Interactive Benchmark for LLM Agents in Long-Context Software Engineering.

Jielin Qiu, Zuxin Liu, Zhiwei Liu, Rithesh Murthy, Jianguo Zhang, Haolin Chen, Shiyu Wang, Ming Zhu, Liangwei Yang, Juntao Tan, Roshan Ram, Akshara Prabhakar, Tulika Awalgaonkar, Zixiang Chen, Zhepeng Cen, Cheng Qian, Shelby Heinecke, Weiran Yao, Silvio Savarese, Caiming Xiong, Huan Wang

CoRR, November, 2025

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels.

Zhepeng Cen, Haolin Chen, Shiyu Wang, Zuxin Liu, Zhiwei Liu, Ding Zhao, Silvio Savarese, Caiming Xiong, Huan Wang, Weiran Yao

CoRR, October, 2025

LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering.

Jielin Qiu, Zuxin Liu, Zhiwei Liu, Rithesh Murthy, Jianguo Zhang, Haolin Chen, Shiyu Wang, Ming Zhu, Liangwei Yang, Juntao Tan, Zhepeng Cen, Cheng Qian, Shelby Heinecke, Weiran Yao, Silvio Savarese, Caiming Xiong, Huan Wang

CoRR, September, 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, May, 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

Trans. Mach. Learn. Res., 2025

Behavior Injection: Preparing Language Models for Reinforcement Learning.

Zhepeng Cen, Yihang Yao, William Han, Zuxin Liu, Ding Zhao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 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

Proceedings of the Findings of the Association for Computational Linguistics, 2025

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, Ding Zhao

Proceedings of the Findings of the Association for Computational Linguistics, 2025

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

J. Data-centric Mach. Learn. Res., 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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Gradient shaping for multi-constraint safe reinforcement learning.

Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Feasibility Consistent Representation Learning for Safe Reinforcement Learning.

Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning from Sparse Offline Datasets via Conservative Density Estimation.

Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning.

Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Constrained Decision Transformer for Offline Safe Reinforcement Learning.

Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability.

Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao

CoRR, 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, Ding Zhao

CoRR, 2022

Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS).

Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Bo Li, Henry Lam, Ding Zhao

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Constrained Variational Policy Optimization for Safe Reinforcement Learning.

Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao

Proceedings of the International Conference on Machine Learning, 2022

2020

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019

Vehicle Trajectory Prediction Using Intention-based Conditional Variational Autoencoder.

Xidong Feng, Zhepeng Cen, Jianming Hu, Yi Zhang

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019