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Jesse Zhang
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2020 – today
- 2024
- [c13]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 - [i17]Yufei Wang, Zhanyi Sun, Jesse Zhang, Zhou Xian, Erdem Biyik, David Held, Zackory Erickson:
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback. CoRR abs/2402.03681 (2024) - [i16]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) - 2023
- [c12]Jesse Zhang, Jiahui Zhang, Karl Pertsch, Ziyi Liu, Xiang Ren, Minsuk Chang, Shao-Hua Sun, Joseph J. Lim:
Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance. CoRL 2023: 302-325 - [c11]Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. NeurIPS 2023 - [i15]Linghan Zhong, Ryan Lindeborg, Jesse Zhang, Joseph J. Lim, Shao-Hua Sun:
Hierarchical Neural Program Synthesis. CoRR abs/2303.06018 (2023) - [i14]Jesse Zhang, Karl Pertsch, Jiahui Zhang, Joseph J. Lim:
SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling. CoRR abs/2306.11886 (2023) - [i13]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) - [i12]Sumedh A. Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. CoRR abs/2310.07899 (2023) - [i11]Jesse Zhang, Jiahui Zhang, Karl Pertsch, Ziyi Liu, Xiang Ren, Minsuk Chang, Shao-Hua Sun, Joseph J. Lim:
Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance. CoRR abs/2310.10021 (2023) - [i10]Taewook Nam, Juyong Lee, Jesse Zhang, Sung Ju Hwang, Joseph J. Lim, Karl Pertsch:
LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers. CoRR abs/2312.08958 (2023) - 2021
- [c10]Jesse Zhang, Haonan Yu, Wei Xu:
Hierarchical Reinforcement Learning by Discovering Intrinsic Options. ICLR 2021 - [c9]Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim:
Learning to Synthesize Programs as Interpretable and Generalizable Policies. NeurIPS 2021: 25146-25163 - [c8]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:
Greenplum: A Hybrid Database for Transactional and Analytical Workloads. SIGMOD Conference 2021: 2530-2542 - [c7]Afzal Godil, Yooyoung Lee, Jon Fiscus, Andrew Delgado, Eliot Godard, Baptiste Chocot, Lukas L. Diduch, Jim Golden, Jesse Zhang:
2020 Sequestered Data Evaluation for Known Activities in Extended Video: Summary and Results. WACV (Workshops) 2021: 51-59 - [i9]Jesse Zhang, Haonan Yu, Wei Xu:
Hierarchical Reinforcement Learning By Discovering Intrinsic Options. CoRR abs/2101.06521 (2021) - [i8]Zhenghua Lyu, Huan Hubert Zhang, Gang Xiong, Haozhou Wang, Gang Guo, Jinbao Chen, Asim Praveen, Yu Yang, Xiaoming Gao, Ashwin Agrawal, Alexandra Wang, Wen Lin, Junfeng Yang, Hao Wu, Xiaoliang Li, Feng Guo, Jiang Wu, Jesse Zhang, Venkatesh Raghavan:
Greenplum: A Hybrid Database for Transactional and Analytical Workloads. CoRR abs/2103.11080 (2021) - [i7]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:
TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains. CoRR abs/2104.13473 (2021) - [i6]Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim:
Learning to Synthesize Programs as Interpretable and Generalizable Policies. CoRR abs/2108.13643 (2021) - 2020
- [c6]Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine:
Chaining Behaviors from Data with Model-Free Reinforcement Learning. CoRL 2020: 2162-2177 - [c5]Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman:
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. ICML 2020: 11055-11065 - [c4]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:
TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains. TRECVID 2020 - [e2]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:
2020 TREC Video Retrieval Evaluation, TRECVID 2020, Gaithersburg, MD, USA, December 8-11, 2020. National Institute of Standards and Technology (NIST) 2020 [contents] - [i5]Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman:
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. CoRR abs/2008.06622 (2020) - [i4]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:
TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval. CoRR abs/2009.09984 (2020) - [i3]Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine:
COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning. CoRR abs/2010.14500 (2020)
2010 – 2019
- 2019
- [c3]Brian H. Yang, Dinesh Jayaraman, Jesse Zhang, Sergey Levine:
REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning. ICRA 2019: 8691-8697 - [c2]Jesse Zhang, Jack Sullivan, Vasudev Venkatesh P. B., Kyle Tse, Andy Yan, John Leyden, Kalyanaraman Shankari, Randy H. Katz:
TripAware: Emotional and Informational Approaches to Encourage Sustainable Transportation via Mobile Applications. BuildSys@SenSys 2019: 183-186 - [c1]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:
TRECVID 2019: An evaluation campaign to benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & retrieval. TRECVID 2019 - [e1]George Awad, Asad A. Butt, Keith Curtis, Yooyoung Lee, Jon Fiscus, Afzal Godil, Andrew Delgado, Jesse Zhang, Eliot Godard, Lukas L. Diduch, Alan F. Smeaton, Yvette Graham, Wessel Kraaij, Georges Quénot:
2019 TREC Video Retrieval Evaluation, TRECVID 2019, Gaithersburg, MD, USA, November 12-13, 2019. National Institute of Standards and Technology (NIST) 2019 [contents] - [i2]Brian H. Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman:
REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning. CoRR abs/1905.07447 (2019) - [i1]Daiyaan Arfeen, Jesse Zhang:
Unsupervised Projection Networks for Generative Adversarial Networks. CoRR abs/1910.00579 (2019)
Coauthor Index
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last updated on 2024-08-08 19:13 CEST by the dblp team
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