Chebotar, Yevgen

20 publications

ICML 2024 Stop Regressing: Training Value Functions via Classification for Scalable Deep RL Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taiga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal

ICML 2023 PaLM-E: An Embodied Multimodal Language Model Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence

CoRL 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

CoRL 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 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

NeurIPS 2023 ReDS: Offline RL with Heteroskedastic Datasets via Support Constraints Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

NeurIPSW 2023 Robotic Offline RL from Internet Videos via Value-Function Pre-Training Chethan Anand Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar

NeurIPS 2022 DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar

ICMLW 2022 DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar

CoRL 2022 Do as I Can, Not as I Say: Grounding Language in Robotic Affordances Brian Ichter, Anthony Brohan, Yevgen Chebotar, Chelsea Finn, Karol Hausman, Alexander Herzog, Daniel Ho, Julian Ibarz, Alex Irpan, Eric Jang, Ryan Julian, Dmitry Kalashnikov, Sergey Levine, Yao Lu, Carolina Parada, Kanishka Rao, Pierre Sermanet, Alexander T Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Mengyuan Yan, Noah Brown, Michael Ahn, Omar Cortes, Nicolas Sievers, Clayton Tan, Sichun Xu, Diego Reyes, Jarek Rettinghouse, Jornell Quiambao, Peter Pastor, Linda Luu, Kuang-Huei Lee, Yuheng Kuang, Sally Jesmonth, Nikhil J. Joshi, Kyle Jeffrey, Rosario Jauregui Ruano, Jasmine Hsu, Keerthana Gopalakrishnan, Byron David, Andy Zeng, Chuyuan Kelly Fu

ICML 2022 How to Leverage Unlabeled Data in Offline Reinforcement Learning Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine

CoRL 2022 Inner Monologue: Embodied Reasoning Through Planning with Language Models Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, Pierre Sermanet, Tomas Jackson, Noah Brown, Linda Luu, Sergey Levine, Karol Hausman, Brian Ichter

NeurIPSW 2022 Offline Reinforcement Learning from Heteroskedastic Data via Support Constraints Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

NeurIPSW 2022 Offline Reinforcement Learning from Heteroskedastic Data via Support Constraints Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

CoRL 2021 AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine

ICML 2021 Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine

NeurIPS 2021 Conservative Data Sharing for Multi-Task Offline Reinforcement Learning Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn

NeurIPSW 2021 Data Sharing Without Rewards in Multi-Task Offline Reinforcement Learning Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Chelsea Finn, Sergey Levine, Karol Hausman

CoRL 2021 Scaling up Multi-Task Robotic Reinforcement Learning Dmitry Kalashnikov, Jake Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, Karol Hausman

ICML 2017 Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning Yevgen Chebotar, Karol Hausman, Marvin Zhang, Gaurav Sukhatme, Stefan Schaal, Sergey Levine

NeurIPS 2017 Multi-Modal Imitation Learning from Unstructured Demonstrations Using Generative Adversarial Nets Karol Hausman, Yevgen Chebotar, Stefan Schaal, Gaurav Sukhatme, Joseph J. Lim