Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL. - Yanchao Sun; Ruijie Zheng; Yongyuan Liang; Furong Huang (ICLR, 2022)

Transfer RL across Observation Feature Spaces via Model-Based Regularization. - Yanchao Sun; Ruijie Zheng; Xiyao Wang; Andrew E. Cohen; Furong Huang (ICLR, 2022)

Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning. - Yongyuan Liang; Yanchao Sun; Ruijie Zheng; Furong Huang (NeurIPS, 2022)

Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems. - Yanchao Sun; Ruijie Zheng; Parisa Hassanzadeh; Yongyuan Liang; Soheil Feizi; Sumitra Ganesh; Furong Huang (CoRR, 2022)

Is Imitation All You Need? Generalized Decision-Making with Dual-Phase Training. - Yao Wei 002; Yanchao Sun; Ruijie Zheng; Sai Vemprala; Rogerio Bonatti; Shuhang Chen; Ratnesh Madaan; Zhongjie Ba; Ashish Kapoor; Shuang Ma (ICCV, 2023)

Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication. - Yanchao Sun; Ruijie Zheng; Parisa Hassanzadeh; Yongyuan Liang; Soheil Feizi; Sumitra Ganesh; Furong Huang (ICLR, 2023)

Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function. - Ruijie Zheng; Xiyao Wang; Huazhe Xu; Furong Huang (ICLR, 2023)

TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning. - Ruijie Zheng; Xiyao Wang; Yanchao Sun; Shuang Ma; Jieyu Zhao 001; Huazhe Xu; Hal Daumé III; Furong Huang (NeurIPS, 2023)

Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations. - Yongyuan Liang; Yanchao Sun; Ruijie Zheng; Xiangyu Liu; Tuomas Sandholm; Furong Huang; Stephen McAleer (CoRR, 2023)

Equal Long-term Benefit Rate: Adapting Static Fairness Notions to Sequential Decision Making. - Yuancheng Xu; Chenghao Deng; Yanchao Sun; Ruijie Zheng; Xiyao Wang; Jieyu Zhao 001; Furong Huang (CoRR, 2023)

Progressively Efficient Learning. - Ruijie Zheng; Khanh Nguyen; Hal Daumé III; Furong Huang; Karthik Narasimhan (CoRR, 2023)

Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations. - Yongyuan Liang; Yanchao Sun; Ruijie Zheng; Xiangyu Liu; Benjamin Eysenbach; Tuomas Sandholm; Furong Huang; Stephen Marcus McAleer (ICLR, 2024)

COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL. - Xiyao Wang; Ruijie Zheng; Yanchao Sun; Ruonan Jia; Wichayaporn Wongkamjan; Huazhe Xu; Furong Huang (ICLR, 2024)

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization. - Guowei Xu 001; Ruijie Zheng; Yongyuan Liang; Xiyao Wang; Zhecheng Yuan; Tianying Ji; Yu Luo; Xiaoyu Liu 003; Jiaxin Yuan; Pu Hua; Shuzhen Li; Yanjie Ze; et al. (ICLR, 2024)

ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization. - Tianying Ji; Yongyuan Liang; Yan Zeng 002; Yu Luo; Guowei Xu 001; Jiawei Guo; Ruijie Zheng; Furong Huang; Fuchun Sun 001; Huazhe Xu (ICML, 2024)

Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate. - Yuancheng Xu; Chenghao Deng; Yanchao Sun; Ruijie Zheng; Xiyao Wang; Jieyu Zhao 001; Furong Huang (ICML, 2024)

PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control. - Ruijie Zheng; Ching-An Cheng; Hal Daumé III; Furong Huang; Andrey Kolobov (ICML, 2024)

Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss. - Ruijie Zheng; Yongyuan Liang; Xiyao Wang; Shuang Ma; Hal Daumé III; Huazhe Xu; John Langford 001; Praveen Palanisamy; Kalyan Shankar Basu; Furong Huang (ICML, 2024)

PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem. - Ruijie Zheng; Ching-An Cheng; Hal Daumé III; Furong Huang; Andrey Kolobov (CoRR, 2024)

Magma: A Foundation Model for Multimodal AI Agents. - Jianwei Yang; Reuben Tan; Qianhui Wu; Ruijie Zheng; Baolin Peng; Yongyuan Liang; Yu Gu 017; Mu Cai; Seonghyeon Ye; Joel Jang; Yuquan Deng; Jianfeng Gao 001 (CVPR, 2025)

TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies. - Ruijie Zheng; Yongyuan Liang; Shuaiyi Huang; Jianfeng Gao 001; Hal Daumé III; Andrey Kolobov; Furong Huang; Jianwei Yang (ICLR, 2025)

Magma: A Foundation Model for Multimodal AI Agents. - Jianwei Yang; Reuben Tan; Qianhui Wu; Ruijie Zheng; Baolin Peng; Yongyuan Liang; Yu Gu 017; Mu Cai; Seonghyeon Ye; Joel Jang; Yuquan Deng; Lars Liden; et al. (CoRR, 2025)

GR00T N1: An Open Foundation Model for Generalist Humanoid Robots. - Johan Bjorck; Fernando Castañeda; Nikita Cherniadev; Xingye Da; Runyu Ding; Linxi; Yu Fang; Dieter Fox; Fengyuan Hu; Spencer Huang; Joel Jang; Zhenyu Jiang 002; et al. (CoRR, 2025)

TREND: Tri-teaching for Robust Preference-based Reinforcement Learning with Demonstrations. - Shuaiyi Huang; Mara Levy; Anubhav Gupta; Daniel Ekpo; Ruijie Zheng; Abhinav Shrivastava (CoRR, 2025)

DreamGen: Unlocking Generalization in Robot Learning through Neural Trajectories. - Joel Jang; Seonghyeon Ye; Zongyu Lin; Jiannan Xiang; Johan Bjorck; Yu Fang; Fengyuan Hu; Spencer Huang; Kaushil Kundalia; Yen-Chen Lin; Loic Magne; Ajay Mandlekar; et al. (CoRR, 2025)

FLARE: Robot Learning with Implicit World Modeling. - Ruijie Zheng; Jing Wang; Scott Reed; Johan Bjorck; Yu Fang; Fengyuan Hu; Joel Jang; Kaushil Kundalia; Zongyu Lin; Loic Magne; Avnish Narayan; You Liang Tan; et al. (CoRR, 2025)

Provably Learning from Language Feedback. - Wanqiao Xu; Allen Nie; Ruijie Zheng; Aditya Modi 002; Adith Swaminathan; Ching-An Cheng (CoRR, 2025)

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control. - Zilin Kang; Chenyuan Hu; Yu Luo; Zhecheng Yuan; Ruijie Zheng; Huazhe Xu (CoRR, 2025)