Sergey Levine

Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning

Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine

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 Singht, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine

Comments See website at https://qtransformer.github.io

Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models

Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Walke, Chelsea Finn, Aviral Kumar, Sergey Levine

Comments 22 pages, 8 figures

Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning

Dhruv Shah, Michael Equi, Blazej Osinski, Fei Xia, Brian Ichter, Sergey Levine

Comments Videos, code, and an interactive Colab notebook that runs in your browser https://sites.google.com/view/lfg-nav/

Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction

Han Qi, Xinyang Geng, Stefano Rando, Iku Ohama, Aviral Kumar, Sergey Levine

Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias

Max Sobol Mark, Archit Sharma, Fahim Tajwar, Rafael Rafailov, Sergey Levine, Chelsea Finn

NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration

Ajay Sridhar, Dhruv Shah, Catherine Glossop, Sergey Levine

Comments Project page https://general-navigation-models.github.io/nomad/

Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts

Amrith Setlur, Don Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine

Journal ref ICLR 2023

Rapid Exploration for Open-World Navigation with Latent Goal Models

Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine

Comments Presented at 5th Annual Conference on Robot Learning (CoRL 2021), London, UK as an Oral Talk. Project page and dataset release at https://sites.google.com/view/recon-robot

Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials

Aviral Kumar, Anikait Singh, Frederik Ebert, Mitsuhiko Nakamoto, Yanlai Yang, Chelsea Finn, Sergey Levine

Robotic Offline RL from Internet Videos via Value-Function Pre-Training

Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar

Comments First three authors contributed equally

Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning

Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine

Comments Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023

REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation

Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine

Comments Accepted at CORL 2023. The first two authors contributed equally

Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios

Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine

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, Alex 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 Ryoo, Grecia Salazar, Pannag Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich

Comments See website at robotics-transformer1.github.io

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

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 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 Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong 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

Comments Website: https://robotics-transformer.github.io/

Contrastive Example-Based Control

Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

Comments This is an updated version of a manuscript that originally appeared at L4DC 2023. The project website is here https://sites.google.com/view/laeo-rl

Journal ref Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:155-169, 2023

A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning

Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

Comments Accepted to ICML 2023. Video (https://www.youtube.com/watch?v=1xlixIHZ0R4) and code (https://github.com/ben-eysenbach/ac-connection)

Adversarial Policies Beat Superhuman Go AIs

Tony T. Wang, Adam Gleave, Tom Tseng, Kellin Pelrine, Nora Belrose, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell

Comments Accepted to ICML 2023, see paper for changelog

Distributionally Adaptive Meta Reinforcement Learning

Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal

Comments NeurIPS 2022

Jump-Start Reinforcement Learning

Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman

Comments 20 pages, 10 figures

Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models

Ted Xiao, Harris Chan, Pierre Sermanet, Ayzaan Wahid, Anthony Brohan, Karol Hausman, Sergey Levine, Jonathan Tompson

Comments Published as a conference paper at RSS 2023

Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective

Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov

Comments ICLR 2023, Project website with code: https://alignedlatentmodels.github.io/

Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts

Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

Comments 15 pages, 5 figures

Understanding the Complexity Gains of Single-Task RL with a Curriculum

Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine

Comments 40 pages, 11 Figures, 13 Tables, International Conference on Machine Learning (ICML) 2023

Predictable MDP Abstraction for Unsupervised Model-Based RL

Seohong Park, Sergey Levine

Comments ICML 2023

Robust and Versatile Bipedal Jumping Control through Reinforcement Learning

Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath

Comments Accepted in Robotics: Science and Systems 2023 (RSS 2023). The accompanying video is at https://youtu.be/aAPSZ2QFB-E

Efficient Online Reinforcement Learning with Offline Data

Philip J. Ball, Laura Smith, Ilya Kostrikov, Sergey Levine

Comments Short Presentation at ICML 2023; to reproduce our results and use our codebase, see https://github.com/ikostrikov/rlpd

The False Promise of Imitating Proprietary LLMs

Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song

Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features

Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

Comments 22 pages, 9 figures