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ORCIDYecheng Jason Ma 0001
Jason Ma 0001
Person information
- affiliation: University of Pennsylvania (UPenn), Department of Computer and Information Science, GRASP Laboratory, Philadelphia, PA, USA
Other persons with the same name
- Jason Ma 0002 — University of California - San Diego (UCSD), Computer Science Engineering Department, La Jolla, CA, USA
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Conference and Workshop Papers
- 2025
[c23]Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton:
Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. ICLR 2025- [c22]Yecheng Jason Ma, Joey Hejna, Chuyuan Fu, Dhruv Shah, Jacky Liang, Zhuo Xu, Sean Kirmani, Peng Xu, Danny Driess, Ted Xiao, Osbert Bastani, Dinesh Jayaraman, Wenhao Yu, Tingnan Zhang, Dorsa Sadigh, Fei Xia:
Vision Language Models are In-Context Value Learners. ICLR 2025 - [c21]Ondrej Biza, Thomas Weng, Lingfeng Sun, Karl Schmeckpeper, Tarik Kelestemur, Yecheng Jason Ma, Robert Platt, Jan-Willem van de Meent, Lawson L. S. Wong:
On-Robot Reinforcement Learning with Goal-Contrastive Rewards. ICRA 2025: 4797-4805 - [c20]Junyao Shi, Zhuolun Zhao, Tianyou Wang, Ian Pedroza, Amy Luo, Jie Wang, Jason Ma, Dinesh Jayaraman:
ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos. ICRA 2025: 16939-16947 - 2024
- [c19]William Liang, Sam Wang, Hung-Ju Wang, Osbert Bastani, Dinesh Jayaraman, Yecheng Jason Ma:
Environment Curriculum Generation via Large Language Models. CoRL 2024: 433-454 - [c18]Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar:
Eureka: Human-Level Reward Design via Coding Large Language Models. ICLR 2024 - [c17]Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew E. Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey T. Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante-Gomez, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 2024: 6892-6903 - [c16]Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs:
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. ICRA 2024: 6973-6980 - [c15]Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman:
Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models. ICRA 2024: 15424-15432 - [c14]Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Yecheng Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R. Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, Jensen Gao, David Antonio Herrera, Minho Heo, Kyle Hsu, Jiaheng Hu, Donovon Jackson, Charlotte Le, Yunshuang Li, Roy Lin, Zehan Ma, Abhiram Maddukuri, Suvir Mirchandani, Daniel Morton, Tony Nguyen, Abigail O'Neill, Rosario Scalise, Derick Seale, Victor Son, Stephen Tian, Emi Tran, Andrew E. Wang, Yilin Wu, Annie Xie, Jingyun Yang, Patrick Yin, Yunchu Zhang, Osbert Bastani, Glen Berseth, Jeannette Bohg
, Ken Goldberg, Abhinav Gupta, Abhishek Gupta, Dinesh Jayaraman, Joseph J. Lim, Jitendra Malik, Roberto Martín-Martín, Subramanian Ramamoorthy, Dorsa Sadigh, Shuran Song, Jiajun Wu, Michael C. Yip, Yuke Zhu, Thomas Kollar, Sergey Levine, Chelsea Finn:
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. Robotics: Science and Systems 2024 - [c13]Yecheng Jason Ma, William Liang, Hung-Ju Wang, Yuke Zhu, Linxi Fan, Osbert Bastani, Dinesh Jayaraman:
DrEureka: Language Model Guided Sim-To-Real Transfer. Robotics: Science and Systems 2024 - 2023
- [c12]Wanqiao Xu, Yecheng Jason Ma, Kan Xu, Hamsa Bastani, Osbert Bastani:
Uniformly Conservative Exploration in Reinforcement Learning. AISTATS 2023: 10856-10870 - [c11]Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang:
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. ICLR 2023 - [c10]Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman:
LIV: Language-Image Representations and Rewards for Robotic Control. ICML 2023: 23301-23320 - [c9]Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman:
Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. L4DC 2023: 259-271 - [c8]Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Tingfan Wu, Jay Vakil, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier:
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? NeurIPS 2023 - 2022
- [c7]Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman:
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. AAAI 2022: 5404-5412 - [c6]Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani:
Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching. ICML 2022: 14639-14663 - [c5]Osbert Bastani, Yecheng Jason Ma, Estelle Shen, Wanqiao Xu:
Regret Bounds for Risk-Sensitive Reinforcement Learning. NeurIPS 2022 - [c4]Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani:
Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression. NeurIPS 2022 - 2021
- [c3]Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani:
Likelihood-Based Diverse Sampling for Trajectory Forecasting. ICCV 2021: 13259-13268 - [c2]Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez:
State Relevance for Off-Policy Evaluation. ICML 2021: 9537-9546 - [c1]Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani:
Conservative Offline Distributional Reinforcement Learning. NeurIPS 2021: 19235-19247
Informal and Other Publications
- 2025
- [i22]Junyao Shi, Zhuolun Zhao, Tianyou Wang, Ian Pedroza, Amy Luo, Jie Wang, Jason Ma, Dinesh Jayaraman:
ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos. CoRR abs/2503.23877 (2025) - 2024
- [i21]Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R. Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, et al.:
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. CoRR abs/2403.12945 (2024) - [i20]Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman:
Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models. CoRR abs/2404.13474 (2024) - [i19]Yecheng Jason Ma, William Liang, Hung-Ju Wang, Sam Wang, Yuke Zhu, Linxi Fan, Osbert Bastani, Dinesh Jayaraman:
DrEureka: Language Model Guided Sim-To-Real Transfer. CoRR abs/2406.01967 (2024) - [i18]Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton:
Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. CoRR abs/2410.13882 (2024) - [i17]Ondrej Biza, Thomas Weng, Lingfeng Sun, Karl Schmeckpeper, Tarik Kelestemur, Yecheng Jason Ma, Robert Platt, Jan-Willem van de Meent, Lawson L. S. Wong:
On-Robot Reinforcement Learning with Goal-Contrastive Rewards. CoRR abs/2410.19989 (2024) - [i16]William Liang, Sam Wang, Hung-Ju Wang, Osbert Bastani, Dinesh Jayaraman, Yecheng Jason Ma:
Eurekaverse: Environment Curriculum Generation via Large Language Models. CoRR abs/2411.01775 (2024) - [i15]Yecheng Jason Ma, Joey Hejna, Ayzaan Wahid, Chuyuan Fu, Dhruv Shah, Jacky Liang, Zhuo Xu, Sean Kirmani, Peng Xu, Danny Driess, Ted Xiao, Jonathan Tompson, Osbert Bastani, Dinesh Jayaraman, Wenhao Yu, Tingnan Zhang, Dorsa Sadigh, Fei Xia:
Vision Language Models are In-Context Value Learners. CoRR abs/2411.04549 (2024) - 2023
- [i14]Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier:
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? CoRR abs/2303.18240 (2023) - [i13]Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman:
TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. CoRR abs/2305.12663 (2023) - [i12]Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman:
LIV: Language-Image Representations and Rewards for Robotic Control. CoRR abs/2306.00958 (2023) - [i11]Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs:
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. CoRR abs/2310.08581 (2023) - [i10]Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar:
Eureka: Human-Level Reward Design via Coding Large Language Models. CoRR abs/2310.12931 (2023) - 2022
- [i9]Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani:
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching. CoRR abs/2202.02433 (2022) - [i8]Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani:
How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression. CoRR abs/2206.03023 (2022) - [i7]Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang:
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. CoRR abs/2210.00030 (2022) - [i6]Osbert Bastani, Yecheng Jason Ma, Estelle Shen, Wanqiao Xu:
Regret Bounds for Risk-Sensitive Reinforcement Learning. CoRR abs/2210.05650 (2022) - 2021
- [i5]Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani:
Conservative Offline Distributional Reinforcement Learning. CoRR abs/2107.06106 (2021) - [i4]Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez:
State Relevance for Off-Policy Evaluation. CoRR abs/2109.06310 (2021) - [i3]Jeevana Priya Inala, Yecheng Jason Ma, Osbert Bastani, Xin Zhang, Armando Solar-Lezama:
Safe Human-Interactive Control via Shielding. CoRR abs/2110.05440 (2021) - [i2]Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman:
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. CoRR abs/2112.07701 (2021) - 2020
- [i1]Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani:
Diverse Sampling for Normalizing Flow Based Trajectory Forecasting. CoRR abs/2011.15084 (2020)
Coauthor Index
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