Sergey Levine

RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes

Kyle Stachowicz, Sergey Levine

Comments In review, RSS 2024

Model-Based Reinforcement Learning for Atari

Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Afroz Mohiuddin, Ryan Sepassi, George Tucker, Henryk Michalewski

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

Comments Project website: https://yay-robot.github.io/

RLIF: Interactive Imitation Learning as Reinforcement Learning

Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine

Comments ICLR 2024

Deep Neural Networks Tend To Extrapolate Predictably

Katie Kang, Amrith Setlur, Claire Tomlin, Sergey Levine

METRA: Scalable Unsupervised RL with Metric-Aware Abstraction

Seohong Park, Oleh Rybkin, Sergey Levine

Comments ICLR 2024

HIQL: Offline Goal-Conditioned RL with Latent States as Actions

Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine

Comments NeurIPS 2023

Stop Regressing: Training Value Functions via Classification for Scalable Deep RL

Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taïga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal

ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL

Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar

Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation

Jonathan Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah, Quan Vuong, Chelsea Finn, Dorsa Sadigh, Sergey Levine

Comments 16 pages, 9 figures

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control

Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M Tseng, Tommaso Biancalani, Sergey Levine

Comments Under review (codes will be released soon)

Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings

Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, Quan Vuong, Tingnan Zhang, Tsang-Wei Edward Lee, Kuang-Huei Lee, Peng Xu, Sean Kirmani, Yuke Zhu, Andy Zeng, Karol Hausman, Nicolas Heess, Chelsea Finn, Sergey Levine, Brian Ichter

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning

Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine

Comments NeurIPS 2023. project page: https://nakamotoo.github.io/Cal-QL

BridgeData V2: A Dataset for Robot Learning at Scale

Homer Walke, Kevin Black, Abraham Lee, Moo Jin Kim, Max Du, Chongyi Zheng, Tony Zhao, Philippe Hansen-Estruch, Quan Vuong, Andre He, Vivek Myers, Kuan Fang, Chelsea Finn, Sergey Levine

Comments 9 pages

Multi-Stage Cable Routing through Hierarchical Imitation Learning

Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, Sergey Levine

Comments T-RO 2024

Training Diffusion Models with Reinforcement Learning

Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine

Comments 23 pages, 16 figures

Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents

Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter

Ignorance is Bliss: Robust Control via Information Gating

Manan Tomar, Riashat Islam, Matthew E. Taylor, Sergey Levine, Philip Bachman

Comments NeurIPS 2023

InfoBot: Transfer and Exploration via the Information Bottleneck

Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew Botvinick, Hugo Larochelle, Yoshua Bengio, Sergey Levine

Comments Accepted at ICLR'19

LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models

Marwa Abdulhai, Isadora White, Charlie Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine

Accelerating Exploration with Unlabeled Prior Data

Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine

Comments 25 pages, 16 figures, 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Multi-Task Imitation Learning for Linear Dynamical Systems

Thomas T. Zhang, Katie Kang, Bruce D. Lee, Claire Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni

Comments Appeared in L4DC 2023. V3: corrected typo in assumptions

Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations

Joey Hong, Sergey Levine, Anca Dragan

Comments 25 pages, 6 figures

Offline RL with Observation Histories: Analyzing and Improving Sample Complexity

Joey Hong, Anca Dragan, Sergey Levine

Comments 21 pages, 4 figures

Confidence-Conditioned Value Functions for Offline Reinforcement Learning

Joey Hong, Aviral Kumar, Sergey Levine

Comments published as a paper in ICLR 2023; 16 pages

Learning to Influence Human Behavior with Offline Reinforcement Learning

Joey Hong, Sergey Levine, Anca Dragan

Comments Published at NeurIPS 2023; 13 pages, 10 figures

Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion

Laura Smith, Yunhao Cao, Sergey Levine

Comments First two authors contributed equally. Project website: https://sites.google.com/berkeley.edu/aprl

SACSoN: Scalable Autonomous Control for Social Navigation

Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine

Comments 11 pages, 15 figures, 4 tables

ViNT: A Foundation Model for Visual Navigation

Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine

Comments Accepted for oral presentation at CoRL 2023