Jesse Zhang

According to our database, Jesse Zhang authored at least 21 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data.

Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J. Lim, Yao Liu, Rasool Fakoor

CoRR, 2024

SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling.

Jesse Zhang, Karl Pertsch, Jiahui Zhang, Joseph J. Lim

Proceedings of the IEEE International Conference on Robotics and Automation, 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

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers.

Taewook Nam, Juyong Lee, Jesse Zhang, Sung Ju Hwang, Joseph J. Lim, Karl Pertsch

CoRR, 2023

Hierarchical Neural Program Synthesis.

Linghan Zhong, Ryan Lindeborg, Jesse Zhang, Joseph J. Lim, Shao-Hua Sun

CoRR, 2023

RoboCLIP: One Demonstration is Enough to Learn Robot Policies.

Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Conference on Robot Learning, 2023

2021

2020 Sequestered Data Evaluation for Known Activities in Extended Video: Summary and Results.

Afzal Godil, Yooyoung Lee, Jon Fiscus, Andrew Delgado, Eliot Godard, Baptiste Chocot, Lukas L. Diduch, Jim Golden, Jesse Zhang

Proceedings of the IEEE Winter Conference on Applications of Computer Vision Workshops, 2021

Greenplum: A Hybrid Database for Transactional and Analytical Workloads.

Zhenghua Lyu, Huan Hubert Zhang, Gang Xiong, Gang Guo, Haozhou Wang, Jinbao Chen, Asim Praveen, Yu Yang, Xiaoming Gao, Alexandra Wang, Wen Lin, Ashwin Agrawal, Junfeng Yang, Hao Wu, Xiaoliang Li, Feng Guo, Jiang Wu, Jesse Zhang, Venkatesh Raghavan

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Learning to Synthesize Programs as Interpretable and Generalizable Policies.

Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Hierarchical Reinforcement Learning by Discovering Intrinsic Options.

Jesse Zhang, Haonan Yu, Wei Xu

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning.

Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine

CoRR, 2020

TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains.

George Awad, Asad A. Butt, Keith Curtis, Jonathan G. Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Jesse Zhang, Eliot Godard, Baptiste Chocot, Lukas L. Diduch, Jeffrey Liu, Alan F. Smeaton, Yvette Graham, Gareth J. F. Jones, Wessel Kraaij, Georges Quénot

Proceedings of the 2020 TREC Video Retrieval Evaluation, 2020

Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings.

Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

Proceedings of the 37th International Conference on Machine Learning, 2020

Chaining Behaviors from Data with Model-Free Reinforcement Learning.

Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Unsupervised Projection Networks for Generative Adversarial Networks.

Daiyaan Arfeen, Jesse Zhang

CoRR, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning.

Brian H. Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman

CoRR, 2019

TRECVID 2019: An evaluation campaign to benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & retrieval.

George Awad, Asad A. Butt, Keith Curtis, Yooyoung Lee, Jonathan G. Fiscus, Afzal Godil, Andrew Delgado, Jesse Zhang, Eliot Godard, Lukas L. Diduch, Alan F. Smeaton, Yvette Graham, Wessel Kraaij, Georges Quénot

Proceedings of the 2019 TREC Video Retrieval Evaluation, 2019

TripAware: Emotional and Informational Approaches to Encourage Sustainable Transportation via Mobile Applications.

Jesse Zhang, Jack Sullivan, Vasudev Venkatesh P. B., Kyle Tse, Andy Yan, John Leyden, Kalyanaraman Shankari, Randy H. Katz

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning.

Brian H. Yang, Dinesh Jayaraman, Jesse Zhang, Sergey Levine

Proceedings of the International Conference on Robotics and Automation, 2019