Karl Pertsch

According to our database, Karl Pertsch authored at least 25 papers between 2017 and 2024.

Collaborative distances:

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

2024

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

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.

CoRR, 2024

Yell At Your Robot: Improving On-the-Fly from Language Corrections.

Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn

CoRR, 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

Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions.

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

CoRR, 2023

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

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

CoRR, 2023

PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection.

Shivin Dass, Karl Pertsch, Hejia Zhang, Youngwoon Lee, Joseph J. Lim, Stefanos Nikolaidis

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

RT-1: Robotics Transformer for Real-World Control at Scale.

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

Proceedings of the Robotics: Science and Systems XIX, Daegu, 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

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

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

Proceedings of the Conference on Robot Learning, 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

Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions.

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

Proceedings of the Conference on Robot Learning, 2023

2022

Task-Induced Representation Learning.

Jun Yamada, Karl Pertsch, Anisha Gunjal, Joseph J. Lim

Proceedings of the Tenth International Conference on Learning Representations, 2022

Skill-based Meta-Reinforcement Learning.

Taewook Nam, Shao-Hua Sun, Karl Pertsch, Sung Ju Hwang, Joseph J. Lim

Proceedings of the Tenth International Conference on Learning Representations, 2022

Cross-Domain Transfer via Semantic Skill Imitation.

Karl Pertsch, Ruta Desai, Vikash Kumar, Franziska Meier, Joseph J. Lim, Dhruv Batra, Akshara Rai

Proceedings of the Conference on Robot Learning, 2022

2021

Demonstration-Guided Reinforcement Learning with Learned Skills.

Karl Pertsch, Youngwoon Lee, Yue Wu, Joseph J. Lim

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

CoRR, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning.

Karl Pertsch, Oleh Rybkin, Jingyun Yang, Shenghao Zhou, Konstantinos G. Derpanis, Kostas Daniilidis, Joseph J. Lim, Andrew Jaegle

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments.

Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert

Proceedings of the 4th Conference on Robot Learning, 2020

Accelerating Reinforcement Learning with Learned Skill Priors.

Karl Pertsch, Youngwoon Lee, Joseph J. Lim

Proceedings of the 4th Conference on Robot Learning, 2020

2019

KeyIn: Discovering Subgoal Structure with Keyframe-based Video Prediction.

Karl Pertsch, Oleh Rybkin, Jingyun Yang, Konstantinos G. Derpanis, Joseph J. Lim, Kostas Daniilidis, Andrew Jaegle

CoRR, 2019

Learning what you can do before doing anything.

Oleh Rybkin, Karl Pertsch, Konstantinos G. Derpanis, Kostas Daniilidis, Andrew Jaegle

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction.

Oleh Rybkin, Karl Pertsch, Andrew Jaegle, Konstantinos G. Derpanis, Kostas Daniilidis

CoRR, 2018

iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects.

Omid Hosseini Jafari, Siva Karthik Mustikovela, Karl Pertsch, Eric Brachmann, Carsten Rother

Proceedings of the Computer Vision - ACCV 2018, 2018

2017

The Best of Both Worlds: Learning Geometry-based 6D Object Pose Estimation.

Omid Hosseini Jafari, Siva Karthik Mustikovela, Karl Pertsch, Eric Brachmann, Carsten Rother

CoRR, 2017