Zhao, Ding

60 publications

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

CVPR 2025 Causal Composition Diffusion Model for Closed-Loop Traffic Generation Haohong Lin, Xin Huang, Tung Phan, David Hayden, Huan Zhang, Ding Zhao, Siddhartha Srinivasa, Eric Wolff, Hongge Chen

AAAI 2025 DiffScene: Diffusion-Based Safety-Critical Scenario Generation for Autonomous Vehicles Chejian Xu, Aleksandr Petiushko, Ding Zhao, Bo Li

MLHC 2025 ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling William Han, Chaojing Duan, Michael Rosenberg, Emerson Liu, Ding Zhao

CoRL 2025 LocoTouch: Learning Dynamic Quadrupedal Transport with Tactile Sensing Changyi Lin, Yuxin Ray Song, Boda Huo, Mingyang Yu, Yikai Wang, Shiqi Liu, Yuxiang Yang, Wenhao Yu, Tingnan Zhang, Jie Tan, Yiyue Luo, Ding Zhao

NeurIPS 2025 Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving Haohong Lin, Yunzhi Zhang, Wenhao Ding, Jiajun Wu, Ding Zhao

NeurIPS 2024 BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-Based Reinforcement Learning Haohong Lin, Wenhao Ding, Jian Chen, Laixi Shi, Jiacheng Zhu, Bo Li, Ding Zhao

DMLR 2024 Benchmarking Robustness of Multimodal Image-Text Models Under Distribution Shift Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li

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

ICML 2024 Feasibility Consistent Representation Learning for Safe Reinforcement Learning Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao

JMLR 2024 Functional Optimal Transport: Regularized mAP Estimation and Domain Adaptation for Functional Data Jiacheng Zhu, Aritra Guha, Dat Do, Mengdi Xu, XuanLong Nguyen, 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

CHIL 2024 Interpretation of Intracardiac Electrograms Through Textual Representations William Han, Diana Guadalupe Gomez, Avi Alok, Chaojing Duan, Michael A Rosenberg, Douglas J Weber, Emerson Liu, 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

CVPR 2024 MMSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos Jielin Qiu, Jiacheng Zhu, William Han, Aditesh Kumar, Karthik Mittal, Claire Jin, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Ding Zhao, Bo Li, Lijuan Wang

ICLR 2024 Meta-Evolve: Continuous Robot Evolution for One-to-Many Policy Transfer Xingyu Liu, Deepak Pathak, Ding Zhao

NeurIPS 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

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

ECCV 2024 RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios Wenhao Ding, Yulong Cao, Ding Zhao, Chaowei Xiao, Marco Pavone

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

ICML 2023 Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-Based Models Wenhao Ding, Tong Che, Ding Zhao, Marco Pavone

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

CoRL 2023 Continual Vision-Based Reinforcement Learning with Group Symmetries Shiqi Liu, Mengdi Xu, Peide Huang, Xilun Zhang, Yongkang Liu, Kentaro Oguchi, Ding Zhao

NeurIPSW 2023 Creative Robot Tool Use with Large Language Models Mengdi Xu, Wenhao Yu, Peide Huang, Shiqi Liu, Xilun Zhang, Yaru Niu, Tingnan Zhang, Fei Xia, Jie Tan, Ding Zhao

ICMLW 2023 DiffScene: Diffusion-Based Safety-Critical Scenario Generation for Autonomous Vehicles Chejian Xu, Ding Zhao, Alberto Sangiovanni-Vincentelli, Bo Li

AISTATS 2023 Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao

ICLR 2023 Hyper-Decision Transformer for Efficient Online Policy Adaptation Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, Chuang Gan

ICML 2023 Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, Xuanlong Nguyen, Bo Li, 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

WACV 2023 LiveSeg: Unsupervised Multimodal Temporal Segmentation of Long Livestream Videos Jielin Qiu, Franck Dernoncourt, Trung Bui, Zhaowen Wang, Ding Zhao, Hailin Jin

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

MLHC 2023 Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision Makiya Nakashima, Donna Salem, HW Wilson Tang, Christopher Nguyen, Tae Hyun Hwang, Ding Zhao, Byung-Hak Kim, Deborah Kwon, David Chen

NeurIPS 2023 Seeing Is Not Believing: Robust Reinforcement Learning Against Spurious Correlation Wenhao Ding, Laixi Shi, Yuejie Chi, 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

ICMLW 2023 Visual-Based Policy Learning with Latent Language Encoding Jielin Qiu, Mengdi Xu, William Han, Bo Li, Ding Zhao

CoRL 2023 What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery Peide Huang, Xilun Zhang, Ziang Cao, Shiqi Liu, Mengdi Xu, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao

NeurIPSW 2022 Benchmarking Robustness Under Distribution Shift of Multimodal Image-Text Models Jielin Qiu, Yi Zhu, Xingjian Shi, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li

ICLR 2022 COPA: Certifying Robust Policies for Offline Reinforcement Learning Against Poisoning Attacks Fan Wu, Linyi Li, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li

ICLR 2022 CROP: Certifying Robust Policies for Reinforcement Learning Through Functional Smoothing Fan Wu, Linyi Li, Zijian Huang, Yevgeniy Vorobeychik, Ding Zhao, Bo Li

CoRL 2022 CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation Wenhao Ding, Haohong Lin, Bo Li, 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

NeurIPS 2022 Curriculum Reinforcement Learning Using Optimal Transport via Gradual Domain Adaptation Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao

NeurIPS 2022 Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

MLHC 2022 GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction Jiacheng Zhu, Jielin Qiu, Zhuolin Yang, Douglas Weber, Michael A. Rosenberg, Emerson Liu, Bo Li, Ding Zhao

NeurIPSW 2022 Hyper-Decision Transformer for Efficient Online Policy Adaptation Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, Chuang Gan

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

CHIL 2022 PhysioMTL: Personalizing Physiological Patterns Using Optimal Transport Multi-Task Regression Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, Xuanlong Nguyen, Shirley You Ren

ICML 2022 Prompting Decision Transformer for Few-Shot Policy Generalization Mengdi Xu, Yikang Shen, Shun Zhang, Yuchen Lu, Ding Zhao, Joshua Tenenbaum, Chuang Gan

IJCAI 2022 Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training Peide Huang, Mengdi Xu, Fei Fang, 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

AISTATS 2021 Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao

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

CVPRW 2019 Density-Adaptive Sampling for Heterogeneous Point Cloud Object Segmentation in Autonomous Vehicle Applications Hasan Asy'ari Arief, Mansur Arief, Manoj Bhat, Ulf Geir Indahl, Håvard Tveite, Ding Zhao