Zhang, Jesse

17 publications

ICLR 2025 HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation Yi Li, Yuquan Deng, Jesse Zhang, Joel Jang, Marius Memmel, Caelan Reed Garrett, Fabio Ramos, Dieter Fox, Anqi Li, Abhishek Gupta, Ankit Goyal

CoRL 2025 ReWiND: Language-Guided Rewards Teach Robot Policies Without New Demonstrations Jiahui Zhang, Yusen Luo, Abrar Anwar, Sumedh Anand Sontakke, Joseph J Lim, Jesse Thomason, Erdem Biyik, Jesse Zhang

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 RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback Yufei Wang, Zhanyi Sun, Jesse Zhang, Zhou Xian, Erdem Biyik, David Held, Zackory Erickson

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

CoRL 2023 Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance Jesse Zhang, Jiahui Zhang, Karl Pertsch, Ziyi Liu, Xiang Ren, Minsuk Chang, Shao-Hua Sun, Joseph J. Lim

NeurIPSW 2023 LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers Taewook Nam, Juyong Lee, Jesse Zhang, Sung Ju Hwang, Joseph J Lim, Karl Pertsch

NeurIPS 2023 RoboCLIP: One Demonstration Is Enough to Learn Robot Policies Sumedh Sontakke, Jesse Zhang, Séb Arnold, Karl Pertsch, Erdem Bıyık, Dorsa Sadigh, Chelsea Finn, Laurent Itti

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

NeurIPSW 2022 SPRINT: Scalable Semantic Policy Pre-Training via Language Instruction Relabeling Jesse Zhang, Karl Pertsch, Jiahui Zhang, Taewook Nam, Sung Ju Hwang, Xiang Ren, Joseph J Lim

NeurIPSW 2022 SPRINT: Scalable Semantic Policy Pre-Training via Language Instruction Relabeling Jesse Zhang, Karl Pertsch, Jiahui Zhang, Taewook Nam, Sung Ju Hwang, Xiang Ren, Joseph J Lim

ICLR 2021 Hierarchical Reinforcement Learning by Discovering Intrinsic Options Jesse Zhang, Haonan Yu, Wei Xu

NeurIPS 2021 Learning to Synthesize Programs as Interpretable and Generalizable Policies Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim

ICML 2020 Cautious Adaptation for Reinforcement Learning in Safety-Critical Settings Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

CoRL 2020 Chaining Behaviors from Data with Model-Free Reinforcement Learning Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine

ICLR 2019 Generalizable Adversarial Training via Spectral Normalization Farzan Farnia, Jesse Zhang, David Tse

NeurIPS 2018 Porcupine Neural Networks: Approximating Neural Network Landscapes Soheil Feizi, Hamid Javadi, Jesse Zhang, David Tse