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2020 – today
- 2024
[j2]Haohong Lin
, Wenhao Ding, Zuxin Liu, Yaru Niu, Jiacheng Zhu, Yuming Niu, Ding Zhao:
Safety-Aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving. IEEE Robotics Autom. Lett. 9(5): 4639-4646 (2024)- [c23]Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao:
Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations. AISTATS 2024: 217-225 - [c22]Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao:
Learning from Sparse Offline Datasets via Conservative Density Estimation. ICLR 2024 - [c21]Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor:
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. ICLR 2024 - [c20]Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao:
Feasibility Consistent Representation Learning for Safe Reinforcement Learning. ICML 2024 - [c19]Fan Yang, Wenxuan Zhou, Zuxin Liu, Ding Zhao, David Held:
Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization. ICRA 2024: 2845-2851 - [c18]Ye Li, Hanjiang Hu, Zuxin Liu, Xiaohao Xu, Xiaonan Huang, Ding Zhao:
Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. ICRA 2024: 9018-9025 - [c17]Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao:
Gradient shaping for multi-constraint safe reinforcement learning. L4DC 2024: 25-39 - [i32]Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao:
Learning from Sparse Offline Datasets via Conservative Density Estimation. CoRR abs/2401.08819 (2024) - [i31]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:
AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning. CoRR abs/2402.15506 (2024) - [i30]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:
AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System. CoRR abs/2402.15538 (2024) - [i29]Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao:
Feasibility Consistent Representation Learning for Safe Reinforcement Learning. CoRR abs/2405.11718 (2024) - [i28]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:
MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases. CoRR abs/2406.10290 (2024) - [i27]Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J. Lim, Yao Liu, Rasool Fakoor:
EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data. CoRR abs/2406.17768 (2024) - [i26]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:
APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets. CoRR abs/2406.18518 (2024) - [i25]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:
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents. CoRR abs/2408.07060 (2024) - [i24]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:
xLAM: A Family of Large Action Models to Empower AI Agent Systems. CoRR abs/2409.03215 (2024) - 2023
- [c16]Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao:
On the Robustness of Safe Reinforcement Learning under Observational Perturbations. ICLR 2023 - [c15]Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Yihang Yao, Hanjiang Hu, Ding Zhao:
Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data. ICML 2023: 21586-21610 - [c14]Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constrained Decision Transformer for Offline Safe Reinforcement Learning. ICML 2023: 21611-21630 - [c13]Hanjiang Hu, Baoquan Yang, Zhijian Qiao, Shiqi Liu, Jiacheng Zhu, Zuxin Liu, Wenhao Ding, Ding Zhao, Hesheng Wang:
SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark Under Multiple Environments. IROS 2023: 11384-11389 - [c12]Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Zhiwei Steven Wu:
Learning Shared Safety Constraints from Multi-task Demonstrations. NeurIPS 2023 - [c11]Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. NeurIPS 2023 - [i23]Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constrained Decision Transformer for Offline Safe Reinforcement Learning. CoRR abs/2302.07351 (2023) - [i22]Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao:
Datasets and Benchmarks for Offline Safe Reinforcement Learning. CoRR abs/2306.09303 (2023) - [i21]Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Zhiwei Steven Wu:
Learning Shared Safety Constraints from Multi-task Demonstrations. CoRR abs/2309.00711 (2023) - [i20]Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao:
Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations. CoRR abs/2309.13150 (2023) - [i19]Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. CoRR abs/2310.03718 (2023) - [i18]Ye Li, Hanjiang Hu, Zuxin Liu, Ding Zhao:
Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. CoRR abs/2310.05245 (2023) - [i17]Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor:
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. CoRR abs/2310.05905 (2023) - [i16]Fan Yang, Wenxuan Zhou, Zuxin Liu, Ding Zhao, David Held:
Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization. CoRR abs/2310.06903 (2023) - [i15]Haohong Lin, Wenhao Ding, Zuxin Liu, Yaru Niu, Jiacheng Zhu, Yuming Niu, Ding Zhao:
Safety-aware Causal Representation for Trustworthy Reinforcement Learning in Autonomous Driving. CoRR abs/2311.10747 (2023) - [i14]Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao:
Gradient Shaping for Multi-Constraint Safe Reinforcement Learning. CoRR abs/2312.15127 (2023) - 2022
- [c10]Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao:
Robustness Certification of Visual Perception Models via Camera Motion Smoothing. CoRL 2022: 1309-1320 - [c9]Hanjiang Hu, Zuxin Liu, Sharad Chitlangia, Akhil Agnihotri, Ding Zhao:
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving. CVPR 2022: 2540-2549 - [c8]Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao:
Constrained Variational Policy Optimization for Safe Reinforcement Learning. ICML 2022: 13644-13668 - [c7]Chejian Xu, Wenhao Ding, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li:
SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles. NeurIPS 2022 - [i13]Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao:
Constrained Variational Policy Optimization for Safe Reinforcement Learning. CoRR abs/2201.11927 (2022) - [i12]Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao:
On the Robustness of Safe Reinforcement Learning under Observational Perturbations. CoRR abs/2205.14691 (2022) - [i11]Chejian Xu, Wenhao Ding, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li:
SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles. CoRR abs/2206.09682 (2022) - [i10]Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao:
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. CoRR abs/2209.08025 (2022) - [i9]Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao:
Robustness Certification of Visual Perception Models via Camera Motion Smoothing. CoRR abs/2210.04625 (2022) - 2021
- [c6]Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Liang Li, Ding Zhao:
Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. ICRA 2021: 10689-10695 - [i8]Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Ding Zhao:
Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. CoRR abs/2101.00531 (2021) - [i7]Sharad Chitlangia, Zuxin Liu, Akhil Agnihotri, Ding Zhao:
Improving Perception via Sensor Placement: Designing Multi-LiDAR Systems for Autonomous Vehicles. CoRR abs/2105.00373 (2021) - 2020
- [j1]Hasan Asy'ari Arief, Mansur Arief, Guilin Zhang, Zuxin Liu, Manoj Bhat, Ulf Geir Indahl, Håvard Tveite, Ding Zhao:
SAnE: Smart Annotation and Evaluation Tools for Point Cloud Data. IEEE Access 8: 131848-131858 (2020) - [c5]Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao:
MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. IROS 2020: 11748-11754 - [c4]Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao:
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. NeurIPS 2020 - [i6]Baiming Chen, Mengdi Xu, Zuxin Liu, Liang Li, Ding Zhao:
Delay-Aware Multi-Agent Reinforcement Learning. CoRR abs/2005.05441 (2020) - [i5]Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao:
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. CoRR abs/2006.11441 (2020) - [i4]Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao:
MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. CoRR abs/2007.15724 (2020) - [i3]Zuxin Liu, Hongyi Zhou, Baiming Chen, Sicheng Zhong, Martial Hebert, Ding Zhao:
Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method. CoRR abs/2010.07968 (2020)
2010 – 2019
- 2019
- [c3]Zuxin Liu, Mansur Arief, Ding Zhao:
Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach. ICRA 2019: 2793-2799 - [c2]Chao Yu, Zuxin Liu, Xin-Jun Liu, Fei Qiao, Yu Wang, Fugui Xie, Qi Wei, Yi Yang:
A DenseNet feature-based loop closure method for visual SLAM system. ROBIO 2019: 258-265 - 2018
- [c1]Chao Yu, Zuxin Liu, Xin-Jun Liu, Fugui Xie, Yi Yang, Qi Wei, Fei Qiao:
DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments. IROS 2018: 1168-1174 - [i2]Zuxin Liu, Mansur Arief, Ding Zhao:
Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach. CoRR abs/1809.05845 (2018) - [i1]Chao Yu, Zuxin Liu, Xinjun Liu, Fugui Xie, Yi Yang, Qi Wei, Fei Qiao:
DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments. CoRR abs/1809.08379 (2018)
Coauthor Index
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last updated on 2024-10-15 21:36 CEST by the dblp team
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