Sergey Levine

GNM: A General Navigation Model to Drive Any Robot

Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, Sergey Levine

Comments Presented at ICRA 2023

IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine

Comments 9 Pages, 4 Figures, 3 Tables

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators

Alexander Herzog, Kanishka Rao, Karol Hausman, Yao Lu, Paul Wohlhart, Mengyuan Yan, Jessica Lin, Montserrat Gonzalez Arenas, Ted Xiao, Daniel Kappler, Daniel Ho, Jarek Rettinghouse, Yevgen Chebotar, Kuang-Huei Lee, Keerthana Gopalakrishnan, Ryan Julian, Adrian Li, Chuyuan Kelly Fu, Bob Wei, Sangeetha Ramesh, Khem Holden, Kim Kleiven, David Rendleman, Sean Kirmani, Jeff Bingham, Jon Weisz, Ying Xu, Wenlong Lu, Matthew Bennice, Cody Fong, David Do, Jessica Lam, Yunfei Bai, Benjie Holson, Michael Quinlan, Noah Brown, Mrinal Kalakrishnan, Julian Ibarz, Peter Pastor, Sergey Levine

Comments Published at Robotics: Science and Systems 2023

Offline RL for Natural Language Generation with Implicit Language Q Learning

Charlie Snell, Ilya Kostrikov, Yi Su, Mengjiao Yang, Sergey Levine

Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Tony Z. Zhao, Vikash Kumar, Sergey Levine, Chelsea Finn

Efficient Deep Reinforcement Learning Requires Regulating Overfitting

Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine

Comments 26 pages, 18 figures, 3 tables, The International Conference on Learning Representations (ICLR) 2023

Learning and Adapting Agile Locomotion Skills by Transferring Experience

Laura Smith, J. Chase Kew, Tianyu Li, Linda Luu, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine

Comments Project website: https://sites.google.com/berkeley.edu/twirl

FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing

Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine

Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes

Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine

Comments Accepted at ICLR 2023. Project website: https://sites.google.com/view/scaling-offlinerl/home

Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks

Kuan Fang, Patrick Yin, Ashvin Nair, Homer Walke, Gengchen Yan, Sergey Levine

Comments CoRL 2022

Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space

Kuan Fang, Patrick Yin, Ashvin Nair, Sergey Levine

Reinforcement Learning from Passive Data via Latent Intentions

Dibya Ghosh, Chethan Bhateja, Sergey Levine

Comments Accompanying website at https://dibyaghosh.com/icvf/

Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement

Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang

Comments 19 pages, 11 figures, Published as a conference paper at the International Conference on Learning Representations 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

Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for Industrial Insertion of Novel Connectors from Vision

Ashvin Nair, Brian Zhu, Gokul Narayanan, Eugen Solowjow, Sergey Levine

Comments 10 pages. To be presented at ICRA 2023

Contrastive Learning as Goal-Conditioned Reinforcement Learning

Benjamin Eysenbach, Tianjun Zhang, Ruslan Salakhutdinov, Sergey Levine

Comments NeurIPS 2022. Code is available on the website: https://ben-eysenbach.github.io/contrastive_rl

Imitating Past Successes can be Very Suboptimal

Benjamin Eysenbach, Soumith Udatha, Sergey Levine, Ruslan Salakhutdinov

Comments NeurIPS 2022

Mismatched No More: Joint Model-Policy Optimization for Model-Based RL

Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov

Comments NeurIPS 2022

Towards Better Few-Shot and Finetuning Performance with Forgetful Causal Language Models

Hao Liu, Xinyang Geng, Lisa Lee, Igor Mordatch, Sergey Levine, Sharan Narang, Pieter Abbeel

Comments Added T-FCM and better FCM results

ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints

Dhruv Shah, Sergey Levine

Comments Best Systems Paper Finalist at XVII Robotics: Science and Systems (RSS 2022), New York City, USA. Project page https://sites.google.com/view/viking-release

Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation

Michael Chang, Thomas L. Griffiths, Sergey Levine

Comments 19 pages, 13 figures, Accepted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

Outcome-Driven Reinforcement Learning via Variational Inference

Tim G. J. Rudner, Vitchyr H. Pong, Rowan McAllister, Yarin Gal, Sergey Levine

Comments Published in Advances in Neural Information Processing Systems 34 (NeurIPS 2021)

Planning with Diffusion for Flexible Behavior Synthesis

Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine

Comments ICML 2022 (long talk). Project page and code at https://diffusion-planning.github.io/

Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance

Kelvin Xu, Zheyuan Hu, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine

Comments First two authors contributed equally

Offline Reinforcement Learning for Visual Navigation

Dhruv Shah, Arjun Bhorkar, Hrish Leen, Ilya Kostrikov, Nick Rhinehart, Sergey Levine

Comments Project page https://sites.google.com/view/revind/home

Learning Robotic Navigation from Experience: Principles, Methods, and Recent Results

Sergey Levine, Dhruv Shah

Comments Final print version is here: https://royalsocietypublishing.org/doi/10.1098/rstb.2021.0447

Journal ref Philosophical Transactions of the Royal Society B, Volume 378 Issue 1869, 2022

Data-Driven Offline Decision-Making via Invariant Representation Learning

Han Qi, Yi Su, Aviral Kumar, Sergey Levine

Comments This is an extended version of the NeurIPS 2022 conference paper titled: "Data-Driven Offline Model-Based Optimization via Invariant Representation Learning"

Offline RL With Realistic Datasets: Heteroskedasticity and Support Constraints

Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

Evolving Reinforcement Learning Algorithms

John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust

Comments ICLR 2021 Oral. See project website at https://sites.google.com/view/evolvingrl

Dual Generator Offline Reinforcement Learning

Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar

Comments NeurIPS 2022