Zuxin Liu - RankMe

89 papers A* 19A 4Misc 2Journal 56Unranked 8

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`	APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay. CoRR Akshara Prabhakar, Zuxin Liu, Ming Zhu, Jianguo Zhang, Tulika Awalgaonkar, Shiyu Wang, Zhiwei Liu, Haolin Chen, Thai Hoang, Juan Carlos Niebles, Shelby Heinecke, Weiran Yao, Huan Wang, Silvio Savarese, Caiming Xiong
2025	A*	`conf`	ActionStudio: A Lightweight Framework for Data and Training of Large Action Models. EMNLP Jianguo Zhang, Thai Hoang, Ming Zhu, Zuxin Liu, Shiyu Wang, Tulika Awalgaonkar, Akshara Prabhakar, Haolin Chen, Weiran Yao, Zhiwei Liu, Juntao Tan, Juan Carlos Niebles, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong
2025	J	`jnl`	ActionStudio: A Lightweight Framework for Data and Training of Large Action Models. CoRR Jianguo Zhang, Thai Hoang, Ming Zhu, Zuxin Liu, Shiyu Wang, Tulika Awalgaonkar, Akshara Prabhakar, Haolin Chen, Weiran Yao, Zhiwei Liu, Juntao Tan, Juan Carlos Niebles, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong
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`	CoDA: Coding LM via Diffusion Adaptation. CoRR Haolin Chen, Shiyu Wang, Can Qin, Bo Pang, Zuxin Liu, Jielin Qiu, Jianguo Zhang, Yingbo Zhou, Zeyuan Chen, Ran Xu, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang, Weiran Yao
2025	A*	`conf`	Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents. ICLR Kexun Zhang, Weiran Yao, Zuxin Liu, Yihao Feng, Zhiwei Liu, Rithesh R. N., Tian Lan, Lei Li, Renze Lou, Jiacheng Xu, Bo Pang, Yingbo Zhou, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong
2025	J	`jnl`	Grounded Test-Time Adaptation for LLM Agents. CoRR Arthur Chen, Zuxin Liu, Jianguo Zhang, Akshara Prabhakar, Zhiwei Liu, Shelby Heinecke, Silvio Savarese, Victor Zhong, Caiming Xiong
2025	—	`conf`	LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback. ACL (Findings) Thai Quoc Hoang, Kung-Hsiang Huang, Shirley Kokane, Jianguo Zhang, Zuxin Liu, Ming Zhu, Jake Grigsby, Tian Lan, Michael S. Ryoo, Chien-Sheng Wu, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong, Juan Carlos Niebles
2025	J	`jnl`	LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback. CoRR Thai Hoang, Kung-Hsiang Huang, Shirley Kokane, Jianguo Zhang, Zuxin Liu, Ming Zhu, Jake Grigsby, Tian Lan, Michael S. Ryoo, Chien-Sheng Wu, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong, Juan Carlos Niebles
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`	MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models. EMNLP (System Demonstrations) Zhiwei Liu, Jielin Qiu, Shiyu Wang, Jianguo Zhang, Zuxin Liu, Roshan Ram, Haolin Chen, Weiran Yao, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong
2025	J	`jnl`	MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models. CoRR Zhiwei Liu, Jielin Qiu, Shiyu Wang, Jianguo Zhang, Zuxin Liu, Roshan Ram, Haolin Chen, Weiran Yao, Huan Wang, Shelby Heinecke, Silvio Savarese, Caiming Xiong
2025	J	`jnl`	MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning. CoRR Yiqing Liang, Jielin Qiu, Wenhao Ding, Zuxin Liu, James Tompkin, Mengdi Xu, Mengzhou Xia, Zhengzhong Tu, Laixi Shi, Jiacheng Zhu
2025	—	`conf`	PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data. ACL (Findings) Juntao Tan, Liangwei Yang, Zuxin Liu, Zhiwei Liu, Rithesh R. N., Tulika Manoj Awalgaonkar, Jianguo Zhang, Weiran Yao, Ming Zhu, Shirley Kokane, Silvio Savarese, Huan Wang, Caiming Xiong, Shelby Heinecke
2025	J	`jnl`	PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data. CoRR Juntao Tan, Liangwei Yang, Zuxin Liu, Zhiwei Liu, Rithesh Murthy, Tulika Manoj Awalgaonkar, Jianguo Zhang, Weiran Yao, Ming Zhu, Shirley Kokane, Silvio Savarese, Huan Wang, Caiming Xiong, Shelby Heinecke
2025	—	`conf`	SlackAgents: Scalable Collaboration of AI Agents in Workspaces. EMNLP (System Demonstrations) Zhiwei Liu, Weiran Yao, Zuxin Liu, Juntao Tan, Jianguo Zhang, Frank Wang, Sukhandeep Nahal, Huan Wang, Shelby Heinecke, Silvio Savarese, Caiming Xiong
2025	J	`jnl`	ToolLibGen: Scalable Automatic Tool Creation and Aggregation for LLM Reasoning. CoRR Murong Yue, Zhiwei Liu, Liangwei Yang, Jianguo Zhang, Zuxin Liu, Haolin Chen, Ziyu Yao, Silvio Savarese, Caiming Xiong, Shelby Heinecke, Huan Wang
2025	J	`jnl`	UserBench: An Interactive Gym Environment for User-Centric Agents. CoRR Cheng Qian, Zuxin Liu, Akshara Prabhakar, Zhiwei Liu, Jianguo Zhang, Haolin Chen, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang
2025	J	`jnl`	UserRL: Training Interactive User-Centric Agent via Reinforcement Learning. CoRR Cheng Qian, Zuxin Liu, Akshara Prabhakar, Jielin Qiu, Zhiwei Liu, Haolin Chen, Shirley Kokane, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang
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
2025	—	`conf`	xLAM: A Family of Large Action Models to Empower AI Agent Systems. NAACL (Long Papers) Jianguo Zhang, Tian Lan, Ming Zhu, Zuxin Liu, Thai Hoang, Shirley Kokane, Weiran Yao, Juntao Tan, Akshara Prabhakar, Haolin Chen, Zhiwei Liu, Yihao Feng, Tulika Manoj Awalgaonkar, Rithesh R. N., Zeyuan Chen, Ran Xu, Juan Carlos Niebles, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong
2025	J	`jnl`	xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning. CoRR Cheng Qian, Zuxin Liu, Shirley Kokane, Akshara Prabhakar, Jielin Qiu, Haolin Chen, Zhiwei Liu, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang
2024	A*	`conf`	APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets. NeurIPS Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley Kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh R. N., Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong
2024	J	`jnl`	APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets. CoRR 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
2024	J	`jnl`	AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System. CoRR Zhiwei Liu, Weiran Yao, Jianguo Zhang, Liangwei Yang, Zuxin Liu, Juntao Tan, Prafulla Kumar Choubey, Tian Lan, Jason Wu, Huan Wang, Shelby Heinecke, Caiming Xiong, Silvio Savarese
2024	J	`jnl`	AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning. CoRR Jianguo Zhang, Tian Lan, Rithesh Murthy, Zhiwei Liu, Weiran Yao, Juntao Tan, Thai Hoang, Liangwei Yang, Yihao Feng, Zuxin Liu, Tulika Manoj Awalgaonkar, Juan Carlos Niebles, Silvio Savarese, Shelby Heinecke, Huan Wang, Caiming Xiong
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	J	`jnl`	Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents. CoRR Kexun Zhang, Weiran Yao, Zuxin Liu, Yihao Feng, Zhiwei Liu, Rithesh Murthy, Tian Lan, Lei Li, Renze Lou, Jiacheng Xu, Bo Pang, Yingbo Zhou, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong
2024	Misc	`conf`	EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data. CoRL Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J. Lim, Yao Liu, Rasool Fakoor
2024	J	`jnl`	EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data. CoRR Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J. Lim, Yao Liu, Rasool Fakoor
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`	Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. ICRA Ye Li, Hanjiang Hu, Zuxin Liu, Xiaohao Xu, Xiaonan Huang, Ding Zhao
2024	J	`jnl`	Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding. CoRR Haolin Chen, Yihao Feng, Zuxin Liu, Weiran Yao, Akshara Prabhakar, Shelby Heinecke, Ricky Ho, Phil Mui, Silvio Savarese, Caiming Xiong, Huan Wang
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	J	`jnl`	MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases. CoRR Rithesh Murthy, Liangwei Yang, Juntao Tan, Tulika Manoj Awalgaonkar, Yilun Zhou, Shelby Heinecke, Sachin Desai, Jason Wu, Ran Xu, Sarah Tan, Jianguo Zhang, Zhiwei Liu, Shirley Kokane, Zuxin Liu, Ming Zhu, Huan Wang, Caiming Xiong, Silvio Savarese
2024	J	`jnl`	PRACT: Optimizing Principled Reasoning and Acting of LLM Agent. CoRR Zhiwei Liu, Weiran Yao, Jianguo Zhang, Rithesh Murthy, Liangwei Yang, Zuxin Liu, Tian Lan, Ming Zhu, Juntao Tan, Shirley Kokane, Thai Hoang, Juan Carlos Niebles, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong
2024	A	`conf`	Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations. AISTATS Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao
2024	A*	`conf`	Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization. ICRA Fan Yang, Wenxuan Zhou, Zuxin Liu, Ding Zhao, David Held
2024	J	`jnl`	Safety-Aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving. IEEE Robotics Autom. Lett. Haohong Lin, Wenhao Ding, Zuxin Liu, Yaru Niu, Jiacheng Zhu, Yuming Niu, Ding Zhao
2024	J	`jnl`	SpecTool: A Benchmark for Characterizing Errors in Tool-Use LLMs. CoRR Shirley Kokane, Ming Zhu, Tulika Awalgaonkar, Jianguo Zhang, Thai Hoang, Akshara Prabhakar, Zuxin Liu, Tian Lan, Liangwei Yang, Juntao Tan, Rithesh Murthy, Weiran Yao, Zhiwei Liu, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong, Silvio Savarese
2024	A*	`conf`	TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. ICLR Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
2024	J	`jnl`	xLAM: A Family of Large Action Models to Empower AI Agent Systems. CoRR Jianguo Zhang, Tian Lan, Ming Zhu, Zuxin Liu, Thai Hoang, Shirley Kokane, Weiran Yao, Juntao Tan, Akshara Prabhakar, Haolin Chen, Zhiwei Liu, Yihao Feng, Tulika Manoj Awalgaonkar, Rithesh Murthy, Eric Hu, Zeyuan Chen, Ran Xu, Juan Carlos Niebles, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong
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	J	`jnl`	Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. CoRR Ye Li, Hanjiang Hu, Zuxin Liu, Ding Zhao
2023	A*	`conf`	Learning Shared Safety Constraints from Multi-task Demonstrations. NeurIPS Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Zhiwei Steven Wu
2023	J	`jnl`	Learning Shared Safety Constraints from Multi-task Demonstrations. CoRR Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Zhiwei Steven Wu
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	J	`jnl`	Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations. CoRR Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao
2023	J	`jnl`	Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization. CoRR Fan Yang, Wenxuan Zhou, Zuxin Liu, Ding Zhao, David Held
2023	J	`jnl`	Safety-aware Causal Representation for Trustworthy Reinforcement Learning in Autonomous Driving. CoRR Haohong Lin, Wenhao Ding, Zuxin Liu, Yaru Niu, Jiacheng Zhu, Yuming Niu, Ding Zhao
2023	A	`conf`	SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark Under Multiple Environments. IROS Hanjiang Hu, Baoquan Yang, Zhijian Qiao, Shiqi Liu, Jiacheng Zhu, Zuxin Liu, Wenhao Ding, Ding Zhao, Hesheng Wang
2023	J	`jnl`	TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. CoRR Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
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	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	A*	`conf`	Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving. CVPR Hanjiang Hu, Zuxin Liu, Sharad Chitlangia, Akhil Agnihotri, 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	Misc	`conf`	Robustness Certification of Visual Perception Models via Camera Motion Smoothing. CoRL Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao
2022	J	`jnl`	Robustness Certification of Visual Perception Models via Camera Motion Smoothing. CoRR Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao
2022	A*	`conf`	SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles. NeurIPS Chejian Xu, Wenhao Ding, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li
2022	J	`jnl`	SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles. CoRR Chejian Xu, Wenhao Ding, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li
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
2021	A*	`conf`	Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. ICRA Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Liang Li, Ding Zhao
2021	J	`jnl`	Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. CoRR Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Ding Zhao
2021	J	`jnl`	Improving Perception via Sensor Placement: Designing Multi-LiDAR Systems for Autonomous Vehicles. CoRR Sharad Chitlangia, Zuxin Liu, Akhil Agnihotri, Ding Zhao
2020	J	`jnl`	Delay-Aware Multi-Agent Reinforcement Learning. CoRR Baiming Chen, Mengdi Xu, Zuxin Liu, Liang Li, Ding Zhao
2020	A	`conf`	MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. IROS Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao
2020	J	`jnl`	MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. CoRR Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao
2020	J	`jnl`	SAnE: Smart Annotation and Evaluation Tools for Point Cloud Data. IEEE Access Hasan Asy'ari Arief, Mansur Arief, Guilin Zhang, Zuxin Liu, Manoj Bhat, Ulf Geir Indahl, Håvard Tveite, Ding Zhao
2020	J	`jnl`	Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method. CoRR Zuxin Liu, Hongyi Zhou, Baiming Chen, Sicheng Zhong, Martial Hebert, Ding Zhao
2020	A*	`conf`	Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. NeurIPS Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao
2020	J	`jnl`	Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. CoRR Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao
2019	—	`conf`	A DenseNet feature-based loop closure method for visual SLAM system. ROBIO Chao Yu, Zuxin Liu, Xin-Jun Liu, Fei Qiao, Yu Wang, Fugui Xie, Qi Wei, Yi Yang
2019	A*	`conf`	Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach. ICRA Zuxin Liu, Mansur Arief, Ding Zhao
2018	A	`conf`	DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments. IROS Chao Yu, Zuxin Liu, Xin-Jun Liu, Fugui Xie, Yi Yang, Qi Wei, Fei Qiao
2018	J	`jnl`	DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments. CoRR Chao Yu, Zuxin Liu, Xinjun Liu, Fugui Xie, Yi Yang, Qi Wei, Fei Qiao
2018	J	`jnl`	Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach. CoRR Zuxin Liu, Mansur Arief, Ding Zhao