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Karl Pertsch
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2020 – today
- 2024
- [i23]Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn:
Yell At Your Robot: Improving On-the-Fly from Language Corrections. CoRR abs/2403.12910 (2024) - [i22]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, et al.:
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. CoRR abs/2403.12945 (2024) - [i21]Xuanlin Li, Kyle Hsu, Jiayuan Gu, Karl Pertsch, Oier Mees, Homer Rich Walke, Chuyuan Fu, Ishikaa Lunawat, Isabel Sieh, Sean Kirmani, Sergey Levine, Jiajun Wu, Chelsea Finn, Hao Su, Quan Vuong, Ted Xiao:
Evaluating Real-World Robot Manipulation Policies in Simulation. CoRR abs/2405.05941 (2024) - [i20]Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Pannag Sanketi, Quan Vuong, Ted Xiao, Dorsa Sadigh, Chelsea Finn, Sergey Levine:
Octo: An Open-Source Generalist Robot Policy. CoRR abs/2405.12213 (2024) - [i19]Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Paul Foster, Grace Lam, Pannag Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, Chelsea Finn:
OpenVLA: An Open-Source Vision-Language-Action Model. CoRR abs/2406.09246 (2024) - 2023
- [c16]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 - [c15]Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, Quan Vuong, Vincent Vanhoucke, Huong T. Tran, Radu Soricut, Anikait Singh, Jaspiar Singh, Pierre Sermanet, Pannag R. Sanketi, Grecia Salazar, Michael S. Ryoo, Krista Reymann, Kanishka Rao, Karl Pertsch, Igor Mordatch, Henryk Michalewski, Yao Lu, Sergey Levine, Lisa Lee, Tsang-Wei Edward Lee, Isabel Leal, Yuheng Kuang, Dmitry Kalashnikov, Ryan Julian, Nikhil J. Joshi, Alex Irpan, Brian Ichter, Jasmine Hsu, Alexander Herzog, Karol Hausman, Keerthana Gopalakrishnan, Chuyuan Fu, Pete Florence, Chelsea Finn, Kumar Avinava Dubey, Danny Driess, Tianli Ding, Krzysztof Marcin Choromanski, Xi Chen, Yevgen Chebotar, Justice Carbajal, Noah Brown, Anthony Brohan, Montserrat Gonzalez Arenas, Kehang Han:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRL 2023: 2165-2183 - [c14]Yevgen Chebotar, Quan Vuong, Karol Hausman, Fei Xia, Yao Lu, Alex Irpan, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Anand Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine:
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRL 2023: 3909-3928 - [c13]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 - [c12]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag R. Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-1: Robotics Transformer for Real-World Control at Scale. Robotics: Science and Systems 2023 - [c11]Shivin Dass, Karl Pertsch, Hejia Zhang, Youngwoon Lee, Joseph J. Lim, Stefanos Nikolaidis:
PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection. Robotics: Science and Systems 2023 - [i18]Jesse Zhang, Karl Pertsch, Jiahui Zhang, Joseph J. Lim:
SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling. CoRR abs/2306.11886 (2023) - [i17]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, Pete Florence, Chuyuan Fu, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Kehang Han, Karol Hausman, Alexander Herzog, Jasmine Hsu, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Lisa Lee, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Henryk Michalewski, Igor Mordatch, Karl Pertsch, Kanishka Rao, Krista Reymann, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong T. Tran, Vincent Vanhoucke, Quan Vuong, Ayzaan Wahid, Stefan Welker, Paul Wohlhart, Jialin Wu, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRR abs/2307.15818 (2023) - [i16]Yevgen Chebotar, Quan Vuong, Alex Irpan, Karol Hausman, Fei Xia, Yao Lu, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine:
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRR abs/2309.10150 (2023) - [i15]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) - [i14]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) - [i13]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) - 2022
- [c10]Karl Pertsch, Ruta Desai, Vikash Kumar, Franziska Meier, Joseph J. Lim, Dhruv Batra, Akshara Rai:
Cross-Domain Transfer via Semantic Skill Imitation. CoRL 2022: 690-700 - [c9]Taewook Nam, Shao-Hua Sun, Karl Pertsch, Sung Ju Hwang, Joseph J. Lim:
Skill-based Meta-Reinforcement Learning. ICLR 2022 - [c8]Jun Yamada, Karl Pertsch, Anisha Gunjal, Joseph J. Lim:
Task-Induced Representation Learning. ICLR 2022 - [i12]Jun Yamada, Karl Pertsch, Anisha Gunjal, Joseph J. Lim:
Task-Induced Representation Learning. CoRR abs/2204.11827 (2022) - [i11]Taewook Nam, Shao-Hua Sun, Karl Pertsch, Sung Ju Hwang, Joseph J. Lim:
Skill-based Meta-Reinforcement Learning. CoRR abs/2204.11828 (2022) - [i10]Shivin Dass, Karl Pertsch, Hejia Zhang, Youngwoon Lee, Joseph J. Lim, Stefanos Nikolaidis:
PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection. CoRR abs/2212.04708 (2022) - [i9]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-1: Robotics Transformer for Real-World Control at Scale. CoRR abs/2212.06817 (2022) - [i8]Karl Pertsch, Ruta Desai, Vikash Kumar, Franziska Meier, Joseph J. Lim, Dhruv Batra, Akshara Rai:
Cross-Domain Transfer via Semantic Skill Imitation. CoRR abs/2212.07407 (2022) - 2021
- [c7]Karl Pertsch, Youngwoon Lee, Yue Wu, Joseph J. Lim:
Demonstration-Guided Reinforcement Learning with Learned Skills. CoRL 2021: 729-739 - [i7]Karl Pertsch, Youngwoon Lee, Yue Wu, Joseph J. Lim:
Demonstration-Guided Reinforcement Learning with Learned Skills. CoRR abs/2107.10253 (2021) - 2020
- [c6]Karl Pertsch, Youngwoon Lee, Joseph J. Lim:
Accelerating Reinforcement Learning with Learned Skill Priors. CoRL 2020: 188-204 - [c5]Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert:
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments. CoRL 2020: 589-603 - [c4]Karl Pertsch, Oleh Rybkin, Jingyun Yang, Shenghao Zhou, Konstantinos G. Derpanis, Kostas Daniilidis, Joseph J. Lim, Andrew Jaegle:
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning. L4DC 2020: 969-979 - [c3]Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine:
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. NeurIPS 2020 - [i6]Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine:
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. CoRR abs/2006.13205 (2020) - [i5]Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert:
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments. CoRR abs/2010.11940 (2020) - [i4]Karl Pertsch, Youngwoon Lee, Joseph J. Lim:
Accelerating Reinforcement Learning with Learned Skill Priors. CoRR abs/2010.11944 (2020)
2010 – 2019
- 2019
- [c2]Oleh Rybkin, Karl Pertsch, Konstantinos G. Derpanis, Kostas Daniilidis, Andrew Jaegle:
Learning what you can do before doing anything. ICLR (Poster) 2019 - [i3]Karl Pertsch, Oleh Rybkin, Jingyun Yang, Konstantinos G. Derpanis, Joseph J. Lim, Kostas Daniilidis, Andrew Jaegle:
KeyIn: Discovering Subgoal Structure with Keyframe-based Video Prediction. CoRR abs/1904.05869 (2019) - 2018
- [c1]Omid Hosseini Jafari, Siva Karthik Mustikovela, Karl Pertsch, Eric Brachmann, Carsten Rother:
iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects. ACCV (3) 2018: 477-492 - [i2]Oleh Rybkin, Karl Pertsch, Andrew Jaegle, Konstantinos G. Derpanis, Kostas Daniilidis:
Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction. CoRR abs/1806.09655 (2018) - 2017
- [i1]Omid Hosseini Jafari, Siva Karthik Mustikovela, Karl Pertsch, Eric Brachmann, Carsten Rother:
The Best of Both Worlds: Learning Geometry-based 6D Object Pose Estimation. CoRR abs/1712.01924 (2017)
Coauthor Index
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last updated on 2024-07-24 20:43 CEST by the dblp team
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