Zhepeng Cen - RankMe

37 papers A* 8Journal 23Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization. CoRR Yihang Yao, Zhepeng Cen, Haohong Lin, Shiqi Liu, Zuxin Liu, Jiacheng Zhu, Zhang-Wei Hong, Laixi Shi, Ding Zhao
2025	J	`jnl`	Behavior Injection: Preparing Language Models for Reinforcement Learning. CoRR Zhepeng Cen, Yihang Yao, William Han, Zuxin Liu, Ding Zhao
2025	J	`jnl`	Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. Trans. Mach. Learn. Res. Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor
2025	J	`jnl`	LoCoBench-Agent: An Interactive Benchmark for LLM Agents in Long-Context Software Engineering. CoRR 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
2025	J	`jnl`	LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering. CoRR 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
2025	—	`conf`	Safety is Not Only About Refusal: Reasoning-Enhanced Fine-tuning for Interpretable LLM Safety. ACL (Findings) Yuyou Zhang, Miao Li, William Han, Yihang Yao, Zhepeng Cen, Ding Zhao
2025	J	`jnl`	Safety is Not Only About Refusal: Reasoning-Enhanced Fine-tuning for Interpretable LLM Safety. CoRR Yuyou Zhang, Miao Li, William Han, Yihang Yao, Zhepeng Cen, Ding Zhao
2025	J	`jnl`	Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework. CoRR William Han, Chaojing Duan, Zhepeng Cen, Yihang Yao, Xiaoyu Song, Atharva Mhaskar, Dylan Leong, Michael A. Rosenberg, Emerson Liu, Ding Zhao
2025	J	`jnl`	Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels. CoRR Zhepeng Cen, Haolin Chen, Shiyu Wang, Zuxin Liu, Zhiwei Liu, Ding Zhao, Silvio Savarese, Caiming Xiong, Huan Wang, Weiran Yao
2025	—	`conf`	Your Language Model May Think Too Rigidly: Achieving Reasoning Consistency with Symmetry-Enhanced Training. ACL (Findings) Yihang Yao, Zhepeng Cen, Miao Li, William Han, Yuyou Zhang, Emerson Liu, Zuxin Liu, Chuang Gan, Ding Zhao
2025	J	`jnl`	Your Language Model May Think Too Rigidly: Achieving Reasoning Consistency with Symmetry-Enhanced Training. CoRR Yihang Yao, Zhepeng Cen, Miao Li, William Han, Yuyou Zhang, Emerson Liu, Zuxin Liu, Chuang Gan, Ding Zhao
2024	J	`jnl`	Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. CoRR Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor
2024	J	`jnl`	Datasets and Benchmarks for Offline Safe Reinforcement Learning. J. Data-centric Mach. Learn. Res. Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao
2024	A*	`conf`	Feasibility Consistent Representation Learning for Safe Reinforcement Learning. ICML Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao
2024	J	`jnl`	Feasibility Consistent Representation Learning for Safe Reinforcement Learning. CoRR Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao
2024	—	`conf`	Gradient shaping for multi-constraint safe reinforcement learning. L4DC Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao
2024	A*	`conf`	Learning from Sparse Offline Datasets via Conservative Density Estimation. ICLR Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao
2024	J	`jnl`	Learning from Sparse Offline Datasets via Conservative Density Estimation. CoRR Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao
2024	A*	`conf`	OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning. NeurIPS Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao
2024	J	`jnl`	OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning. CoRR Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao
2023	A*	`conf`	Constrained Decision Transformer for Offline Safe Reinforcement Learning. ICML Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao
2023	J	`jnl`	Constrained Decision Transformer for Offline Safe Reinforcement Learning. CoRR Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao
2023	A*	`conf`	Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. NeurIPS Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao
2023	J	`jnl`	Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. CoRR Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao
2023	J	`jnl`	Datasets and Benchmarks for Offline Safe Reinforcement Learning. CoRR Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao
2023	J	`jnl`	Gradient Shaping for Multi-Constraint Safe Reinforcement Learning. CoRR Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao
2023	A*	`conf`	On the Robustness of Safe Reinforcement Learning under Observational Perturbations. ICLR Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao
2023	A*	`conf`	Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data. ICML Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Yihang Yao, Hanjiang Hu, Ding Zhao
2022	—	`conf`	Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS). ITSC Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Bo Li, Henry Lam, Ding Zhao
2022	A*	`conf`	Constrained Variational Policy Optimization for Safe Reinforcement Learning. ICML Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao
2022	J	`jnl`	Constrained Variational Policy Optimization for Safe Reinforcement Learning. CoRR Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao
2022	J	`jnl`	On the Robustness of Safe Reinforcement Learning under Observational Perturbations. CoRR Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao
2022	J	`jnl`	Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling. CoRR Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Henry Lam, Bo Li, Ding Zhao
2022	J	`jnl`	Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. CoRR Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao
2020	J	`jnl`	Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora. CoRR Hancheng Cao, Mengjie Cheng, Zhepeng Cen, Daniel A. McFarland, Xiang Ren
2020	—	`conf`	Will this Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora. EMNLP (Findings) Hancheng Cao, Mengjie Cheng, Zhepeng Cen, Daniel A. McFarland, Xiang Ren
2019	—	`conf`	Vehicle Trajectory Prediction Using Intention-based Conditional Variational Autoencoder. ITSC Xidong Feng, Zhepeng Cen, Jianming Hu, Yi Zhang