Liu, Zuxin

28 publications

NeurIPS 2025 APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay Akshara Prabhakar, Zuxin Liu, Ming Zhu, Jianguo Zhang, Tulika Manoj Awalgaonkar, Shiyu Wang, Zhiwei Liu, Haolin Chen, Thai Quoc Hoang, Juan Carlos Niebles, Shelby Heinecke, Weiran Yao, Huan Wang, Silvio Savarese, Caiming Xiong

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

ICLR 2025 Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents Kexun Zhang, Weiran Yao, Zuxin Liu, Yihao Feng, Zhiwei Liu, R N Rithesh, Tian Lan, Lei Li, Renze Lou, Jiacheng Xu, Bo Pang, Yingbo Zhou, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong

ICLRW 2025 ToolScan: A Benchmark for Characterizing Errors in Tool-Use LLMs Shirley Kokane, Ming Zhu, Tulika Manoj Awalgaonkar, Jianguo Zhang, Akshara Prabhakar, Thai Quoc Hoang, Zuxin Liu, R N Rithesh, Liangwei Yang, Weiran Yao, Juntao Tan, Zhiwei Liu, Huan Wang, Juan Carlos Niebles, Shelby Heinecke, Caiming Xiong, Silvio Savarese

NeurIPS 2024 APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley Kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh Murthy, Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong

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

CoRL 2024 EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J Lim, Yao Liu, Rasool Fakoor

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

AISTATS 2024 Pixel-Wise Smoothing for Certified Robustness Against Camera Motion Perturbations Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao

ICLR 2024 TAIL: Task-Specific Adapters for Imitation Learning with Large Pretrained Models Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor

ICLRW 2024 The Agent Ohana: Designing Unified Data and Training Pipeline for Effective Agent Learning Jianguo Zhang, Tian Lan, R N Rithesh, Zhiwei Liu, Weiran Yao, Juntao Tan, Thai Quoc Hoang, Liangwei Yang, Yihao Feng, Zuxin Liu, Ming Zhu, Tulika Manoj Awalgaonkar, Juan Carlos Niebles, Silvio Savarese, Shelby Heinecke, Huan Wang, Caiming Xiong

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

NeurIPS 2023 Learning Shared Safety Constraints from Multi-Task Demonstrations Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Steven Z. Wu

ICMLW 2023 Learning Shared Safety Constraints from Multi-Task Demonstrations Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Steven Wu

ICMLW 2023 Learning Shared Safety Constraints from Multi-Task Demonstrations Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Steven Wu

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

NeurIPSW 2023 TAIL: Task-Specific Adapters for Imitation Learning with Large Pretrained Models Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor

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

CVPR 2022 Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving Hanjiang Hu, Zuxin Liu, Sharad Chitlangia, Akhil Agnihotri, 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

CoRL 2022 Robustness Certification of Visual Perception Models via Camera Motion Smoothing Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao

NeurIPS 2022 SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles Chejian Xu, Wenhao Ding, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li

NeurIPS 2020 Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao