Sergey Levine
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
337
Venues
11
Active years
2012–2026
Best venue rank
A*
Where they publish
Papers
Showing the 300 most recent indexed papers.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Cliqueformer: Model-Based Optimization with Structured Transformers. | Jakub Grudzien Kuba, Pieter Abbeel, Sergey Levine |
| 2025 | ICLR | Adding Conditional Control to Diffusion Models with Reinforcement Learning. | Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Sun-Yuan Kung, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali |
| 2025 | ICLR | Digi-Q: Learning VLM Q-Value Functions for Training Device-Control Agents. | Hao Bai, Yifei Zhou, Li Erran Li, Sergey Levine, Aviral Kumar |
| 2025 | ICLR | One Step Diffusion via Shortcut Models. | Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel |
| 2025 | ICLR | Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning. | Joey Hong, Anca D. Dragan, Sergey Levine |
| 2025 | ICLR | OGBench: Benchmarking Offline Goal-Conditioned RL. | Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine |
| 2025 | ICLR | Language Guided Skill Discovery. | Seungeun Rho, Laura Smith, Tianyu Li, Sergey Levine, Xue Bin Peng, Sehoon Ha |
| 2025 | ICLR | Prioritized Generative Replay. | Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine, Alexei A. Efros |
| 2025 | ICLR | Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design. | Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Aviv Regev, Hanchen Wang, Tommaso Biancalani |
| 2025 | ICLR | Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data. | Zhiyuan Zhou, Andy Peng, Qiyang Li, Sergey Levine, Aviral Kumar |
| 2025 | ICML | LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models. | Marwa Abdulhai, Isadora White, Charlie Victor Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine |
| 2025 | ICML | SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training. | Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V. Le, Sergey Levine, Yi Ma |
| 2025 | ICML | What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning? | Katie Kang, Amrith Setlur, Dibya Ghosh, Jacob Steinhardt, Claire J. Tomlin, Sergey Levine, Aviral Kumar |
| 2025 | ICML | Flow Q-Learning. | Seohong Park, Qiyang Li, Sergey Levine |
| 2025 | ICML | Value-Based Deep RL Scales Predictably. | Oleh Rybkin, Michal Nauman, Preston Fu, Charlie Victor Snell, Pieter Abbeel, Sergey Levine, Aviral Kumar |
| 2025 | ICML | Scaling Test-Time Compute Without Verification or RL is Suboptimal. | Amrith Setlur, Nived Rajaraman, Sergey Levine, Aviral Kumar |
| 2025 | ICML | Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models. | Lucy Xiaoyang Shi, Brian Ichter, Michael Robert Equi, Liyiming Ke, Karl Pertsch, Quan Vuong, James Tanner, Anna Walling, Haohuan Wang, Niccolo Fusai, Adrian Li-Bell, Danny Driess, Lachy Groom, Sergey Levine, Chelsea Finn |
| 2025 | ICML | Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design. | Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani |
| 2025 | ICML | Behavioral Exploration: Learning to Explore via In-Context Adaptation. | Andrew Wagenmaker, Zhiyuan Zhou, Sergey Levine |
| 2025 | ICML | Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration. | Max Wilcoxson, Qiyang Li, Kevin Frans, Sergey Levine |
| 2025 | ICML | Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents. | Yifei Zhou, Qianlan Yang, Kaixiang Lin, Min Bai, Xiong Zhou, Yu-Xiong Wang, Sergey Levine, Li Erran Li |
| 2025 | ICRA | Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models. | Annie S. Chen, Alec M. Lessing, Andy Tang, Govind Chada, Laura Smith, Sergey Levine, Chelsea Finn |
| 2025 | ICRA | The Ingredients for Robotic Diffusion Transformers. | Sudeep Dasari, Oier Mees, Sebastian Zhao, Mohan Kumar Srirama, Sergey Levine |
| 2025 | ICRA | GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. | Kyle Beltran Hatch, Ashwin Balakrishna, Oier Mees, Suraj Nair, Seohong Park, Blake Wulfe, Masha Itkina, Benjamin Eysenbach, Sergey Levine, Thomas Kollar, Benjamin Burchfiel |
| 2025 | ICRA | Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding. | Joshua Jones, Oier Mees, Carmelo Sferrazza, Kyle Stachowicz, Pieter Abbeel, Sergey Levine |
| 2025 | ICRA | Learning Visuotactile Skills With Two Multifingered Hands. | Toru Lin, Yu Zhang, Qiyang Li, Haozhi Qi, Brent Yi, Sergey Levine, Jitendra Malik |
| 2024 | AISTATS | Functional Graphical Models: Structure Enables Offline Data-Driven Optimization. | Kuba Grudzien Kuba, Masatoshi Uehara, Sergey Levine, Pieter Abbeel |
| 2024 | CoRL | Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation. | Ria Doshi, Homer Rich Walke, Oier Mees, Sudeep Dasari, Sergey Levine |
| 2024 | CoRL | LeLaN: Learning A Language-Conditioned Navigation Policy from In-the-Wild Video. | Noriaki Hirose, Catherine Glossop, Ajay Sridhar, Oier Mees, Sergey Levine |
| 2024 | CoRL | SELFI: Autonomous Self-Improvement with RL for Vision-Based Navigation around People. | Noriaki Hirose, Dhruv Shah, Kyle Stachowicz, Ajay Sridhar, Sergey Levine |
| 2024 | CoRL | OpenVLA: An Open-Source Vision-Language-Action Model. | Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Paul Foster, Pannag R. Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, Chelsea Finn |
| 2024 | CoRL | Evaluating Real-World Robot Manipulation Policies in Simulation. | Xuanlin Li, Kyle Hsu, Jiayuan Gu, Oier Mees, Karl Pertsch, Homer Rich Walke, Chuyuan Fu, Ishikaa Lunawat, Isabel Sieh, Sean Kirmani, Sergey Levine, Jiajun Wu, Chelsea Finn, Hao Su, Quan Vuong, Ted Xiao |
| 2024 | CoRL | Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation. | Vivek Myers, Chunyuan Zheng, Oier Mees, Kuan Fang, Sergey Levine |
| 2024 | CoRL | Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance. | Mitsuhiko Nakamoto, Oier Mees, Aviral Kumar, Sergey Levine |
| 2024 | CoRL | Lifelong Autonomous Improvement of Navigation Foundation Models in the Wild. | Kyle Stachowicz, Lydia Ignatova, Sergey Levine |
| 2024 | CoRL | Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. | Zhuo Xu, Hao-Tien Lewis Chiang, Zipeng Fu, Mithun George Jacob, Tingnan Zhang, Tsang-Wei Edward Lee, Wenhao Yu, Connor Schenck, David Rendleman, Dhruv Shah, Fei Xia, Jasmine Hsu, Jonathan Hoech, Pete Florence, Sean Kirmani, Sumeet Singh, Vikas Sindhwani, Carolina Parada, Chelsea Finn, Peng Xu, Sergey Levine, Jie Tan |
| 2024 | CoRL | Robotic Control via Embodied Chain-of-Thought Reasoning. | Michal Zawalski, William Chen, Karl Pertsch, Oier Mees, Chelsea Finn, Sergey Levine |
| 2024 | CoRL | Autonomous Improvement of Instruction Following Skills via Foundation Models. | Zhiyuan Zhou, Pranav Atreya, Abraham Lee, Homer Rich Walke, Oier Mees, Sergey Levine |
| 2024 | ICLR | Training Diffusion Models with Reinforcement Learning. | Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine |
| 2024 | ICLR | Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models. | Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Rich Walke, Chelsea Finn, Aviral Kumar, Sergey Levine |
| 2024 | ICLR | Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features. | Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn |
| 2024 | ICLR | The False Promise of Imitating Proprietary Language Models. | Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song |
| 2024 | ICLR | Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. | Joey Hong, Anca D. Dragan, Sergey Levine |
| 2024 | ICLR | Deep Neural Networks Tend To Extrapolate Predictably. | Katie Kang, Amrith Setlur, Claire J. Tomlin, Sergey Levine |
| 2024 | ICLR | RLIF: Interactive Imitation Learning as Reinforcement Learning. | Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine |
| 2024 | ICLR | METRA: Scalable Unsupervised RL with Metric-Aware Abstraction. | Seohong Park, Oleh Rybkin, Sergey Levine |
| 2024 | ICLR | Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data. | Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine |
| 2024 | ICML | Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. | Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter |
| 2024 | ICML | Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. | Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal |
| 2024 | ICML | Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings. | Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine |
| 2024 | ICML | Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. | Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach |
| 2024 | ICML | 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 |
| 2024 | ICML | Foundation Policies with Hilbert Representations. | Seohong Park, Tobias Kreiman, Sergey Levine |
| 2024 | ICML | Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models. | Amrith Setlur, Saurabh Garg, Virginia Smith, Sergey Levine |
| 2024 | ICML | Feedback Efficient Online Fine-Tuning of Diffusion Models. | Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani |
| 2024 | ICML | Learning to Explore in POMDPs with Informational Rewards. | Annie Xie, Logan M. Bhamidipaty, Evan Zheran Liu, Joey Hong, Sergey Levine, Chelsea Finn |
| 2024 | ICML | ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL. | Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar |
| 2024 | ICRA | Robotic Offline RL from Internet Videos via Value-Function Learning. | Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar |
| 2024 | ICRA | SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. | Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine |
| 2024 | ICRA | Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. | Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew E. Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schlkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Bchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey T. Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, Joo Silvrio, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Snderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martn-Martn, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante-Gomez, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin |
| 2023 | CoRL | 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 |
| 2023 | CoRL | REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. | Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine |
| 2023 | CoRL | Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning. | Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine |
| 2023 | CoRL | Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. | Vivek Myers, Andre Wang He, Kuan Fang, Homer Rich Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine |
| 2023 | CoRL | Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning. | Dhruv Shah, Michael Robert Equi, Blazej Osinski, Fei Xia, Brian Ichter, Sergey Levine |
| 2023 | CoRL | ViNT: A Foundation Model for Visual Navigation. | Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine |
| 2023 | CoRL | FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing. | Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine |
| 2023 | CoRL | BridgeData V2: A Dataset for Robot Learning at Scale. | Homer Rich Walke, Kevin Black, Tony Z. Zhao, Quan Vuong, Chongyi Zheng, Philippe Hansen-Estruch, Andre Wang He, Vivek Myers, Moo Jin Kim, Max Du, Abraham Lee, Kuan Fang, Chelsea Finn, Sergey Levine |
| 2023 | CoRL | 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 |
| 2023 | ICLR | Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. | Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang |
| 2023 | ICLR | Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. | Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov |
| 2023 | ICLR | Confidence-Conditioned Value Functions for Offline Reinforcement Learning. | Joey Hong, Aviral Kumar, Sergey Levine |
| 2023 | ICLR | Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes. | Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine |
| 2023 | ICLR | Efficient Deep Reinforcement Learning Requires Regulating Overfitting. | Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine |
| 2023 | ICLR | Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. | Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine |
| 2023 | ICLR | Offline RL for Natural Language Generation with Implicit Language Q Learning. | Charlie Snell, Ilya Kostrikov, Yi Su, Sherry Yang, Sergey Levine |
| 2023 | ICML | Efficient Online Reinforcement Learning with Offline Data. | Philip J. Ball, Laura Smith, Ilya Kostrikov, Sergey Levine |
| 2023 | ICML | 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 |
| 2023 | ICML | A Connection between One-Step RL and Critic Regularization in Reinforcement Learning. | Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov |
| 2023 | ICML | Reinforcement Learning from Passive Data via Latent Intentions. | Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine |
| 2023 | ICML | Understanding the Complexity Gains of Single-Task RL with a Curriculum. | Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine |
| 2023 | ICML | Predictable MDP Abstraction for Unsupervised Model-Based RL. | Seohong Park, Sergey Levine |
| 2023 | ICML | Jump-Start Reinforcement Learning. | Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Josphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman |
| 2023 | ICML | Adversarial Policies Beat Superhuman Go AIs. | Tony Tong Wang, Adam Gleave, Tom Tseng, Kellin Pelrine, Nora Belrose, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell |
| 2023 | ICRA | Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. | Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman |
| 2023 | ICRA | ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation. | Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine |
| 2023 | ICRA | 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 |
| 2022 | CoRL | Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks. | Kuan Fang, Patrick Yin, Ashvin Nair, Homer Walke, Gengchen Yan, Sergey Levine |
| 2022 | CoRL | GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots. | Gilbert Feng, Hongbo Zhang, Zhongyu Li, Xue Bin Peng, Bhuvan Basireddy, Linzhu Yue, Zhitao Song, Lizhi Yang, Yunhui Liu, Koushil Sreenath, Sergey Levine |
| 2022 | CoRL | 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 |
| 2022 | CoRL | 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 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 |
| 2022 | CoRL | Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty. | Charles Packer, Nicholas Rhinehart, Rowan Thomas McAllister, Matthew A. Wright, Xin Wang, Jeff He, Sergey Levine, Joseph E. Gonzalez |
| 2022 | CoRL | Offline Reinforcement Learning for Visual Navigation. | Dhruv Shah, Arjun Bhorkar, Hrishit Leen, Ilya Kostrikov, Nicholas Rhinehart, Sergey Levine |
| 2022 | CoRL | LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action. | Dhruv Shah, Blazej Osinski, Brian Ichter, Sergey Levine |
| 2022 | CoRL | Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning. | Homer Walke, Jonathan Yang, Albert Yu, Aviral Kumar, Jedrzej Orbik, Avi Singh, Sergey Levine |
| 2022 | ICLR | CoMPS: Continual Meta Policy Search. | Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine |
| 2022 | ICLR | Information Prioritization through Empowerment in Visual Model-based RL. | Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine |
| 2022 | ICLR | RvS: What is Essential for Offline RL via Supervised Learning? | Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine |
| 2022 | ICLR | Maximum Entropy RL (Provably) Solves Some Robust RL Problems. | Benjamin Eysenbach, Sergey Levine |
| 2022 | ICLR | The Information Geometry of Unsupervised Reinforcement Learning. | Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine |
| 2022 | ICLR | Offline Reinforcement Learning with Implicit Q-Learning. | Ilya Kostrikov, Ashvin Nair, Sergey Levine |
| 2022 | ICLR | DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. | Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine |
| 2022 | ICLR | Should I Run Offline Reinforcement Learning or Behavioral Cloning? | Aviral Kumar, Joey Hong, Anikait Singh, Sergey Levine |
| 2022 | ICLR | Data-Driven Offline Optimization for Architecting Hardware Accelerators. | Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine |
| 2022 | ICLR | Extending the WILDS Benchmark for Unsupervised Adaptation. | Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang |
| 2022 | ICLR | Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning. | Dhruv Shah, Peng Xu, Yao Lu, Ted Xiao, Alexander Toshev, Sergey Levine, Brian Ichter |
| 2022 | ICLR | Autonomous Reinforcement Learning: Formalism and Benchmarking. | Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn |
| 2022 | ICLR | TRAIL: Near-Optimal Imitation Learning with Suboptimal Data. | Mengjiao Yang, Sergey Levine, Ofir Nachum |
| 2022 | ICLR | C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. | Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez |
| 2022 | ICML | Offline RL Policies Should Be Trained to be Adaptive. | Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine |
| 2022 | ICML | Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning. | Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine |
| 2022 | ICML | Planning with Diffusion for Flexible Behavior Synthesis. | Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine |
| 2022 | ICML | Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control. | Katie Kang, Paula Gradu, Jason J. Choi, Michael Janner, Claire J. Tomlin, Sergey Levine |
| 2022 | ICML | Offline Meta-Reinforcement Learning with Online Self-Supervision. | Vitchyr H. Pong, Ashvin Nair, Laura Smith, Catherine Huang, Sergey Levine |
| 2022 | ICML | Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization. | Brandon Trabucco, Xinyang Geng, Aviral Kumar, Sergey Levine |
| 2022 | ICML | How to Leverage Unlabeled Data in Offline Reinforcement Learning. | Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine |
| 2022 | ICRA | ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning. | Sean Chen, Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine |
| 2022 | ICRA | Hybrid Imitative Planning with Geometric and Predictive Costs in Off-road Environments. | Nitish Dashora, Daniel Shin, Dhruv Shah, Henry A. Leopold, David D. Fan, Ali-Akbar Agha-Mohammadi, Nicholas Rhinehart, Sergey Levine |
| 2022 | ICRA | Control-Aware Prediction Objectives for Autonomous Driving. | Rowan McAllister, Blake Wulfe, Jean Mercat, Logan Ellis, Sergey Levine, Adrien Gaidon |
| 2022 | IROS | Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space. | Kuan Fang, Patrick Yin, Ashvin Nair, Sergey Levine |
| 2021 | CoRL | BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning. | Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, Chelsea Finn |
| 2021 | CoRL | Scaling Up Multi-Task Robotic Reinforcement Learning. | Dmitry Kalashnikov, Jake Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, Karol Hausman |
| 2021 | CoRL | Hierarchically Integrated Models: Learning to Navigate from Heterogeneous Robots. | Katie Kang, Gregory Kahn, Sergey Levine |
| 2021 | CoRL | A Workflow for Offline Model-Free Robotic Reinforcement Learning. | Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine |
| 2021 | CoRL | Understanding the World Through Action. | Sergey Levine |
| 2021 | CoRL | 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 |
| 2021 | CoRL | Rapid Exploration for Open-World Navigation with Latent Goal Models. | Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine |
| 2021 | CoRL | Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation. | Charles Sun, Jedrzej Orbik, Coline Manon Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine |
| 2021 | ICLR | Learning Invariant Representations for Reinforcement Learning without Reconstruction. | Amy Zhang, Rowan Thomas McAllister, Roberto Calandra, Yarin Gal, Sergey Levine |
| 2021 | ICLR | OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. | Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum |
| 2021 | ICLR | SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments. | Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine |
| 2021 | ICLR | Conservative Safety Critics for Exploration. | Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg |
| 2021 | ICLR | Evolving Reinforcement Learning Algorithms. | John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust |
| 2021 | ICLR | Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. | Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov |
| 2021 | ICLR | C-Learning: Learning to Achieve Goals via Recursive Classification. | Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine |
| 2021 | ICLR | Benchmarks for Deep Off-Policy Evaluation. | Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine |
| 2021 | ICLR | Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation. | Justin Fu, Sergey Levine |
| 2021 | ICLR | X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback. | Jensen Gao, Siddharth Reddy, Glen Berseth, Nicholas Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca D. Dragan, Sergey Levine |
| 2021 | ICLR | Learning to Reach Goals via Iterated Supervised Learning. | Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine |
| 2021 | ICLR | Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. | Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer |
| 2021 | ICLR | Recurrent Independent Mechanisms. | Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schlkopf |
| 2021 | ICLR | Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. | Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine |
| 2021 | ICLR | Parrot: Data-Driven Behavioral Priors for Reinforcement Learning. | Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine |
| 2021 | ICLR | Model-Based Visual Planning with Self-Supervised Functional Distances. | Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine |
| 2021 | ICML | Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment. | Michael Chang, Sidhant Kaushik, Sergey Levine, Tom Griffiths |
| 2021 | ICML | 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 Julian, Chelsea Finn, Sergey Levine |
| 2021 | ICML | Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning. | Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu |
| 2021 | ICML | PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. | Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar |
| 2021 | ICML | Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning. | Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu |
| 2021 | ICML | WILDS: A Benchmark of in-the-Wild Distribution Shifts. | Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran S. Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang |
| 2021 | ICML | MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning. | Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr H. Pong, Aurick Zhou, Justin Yu, Sergey Levine |
| 2021 | ICML | Offline Meta-Reinforcement Learning with Advantage Weighting. | Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn |
| 2021 | ICML | Emergent Social Learning via Multi-agent Reinforcement Learning. | Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques |
| 2021 | ICML | Simple and Effective VAE Training with Calibrated Decoders. | Oleh Rybkin, Kostas Daniilidis, Sergey Levine |
| 2021 | ICML | Model-Based Reinforcement Learning via Latent-Space Collocation. | Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine |
| 2021 | ICML | Conservative Objective Models for Effective Offline Model-Based Optimization. | Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine |
| 2021 | ICML | Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation. | Aurick Zhou, Sergey Levine |
| 2021 | ICRA | SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning. | Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan |
| 2021 | ICRA | Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention. | Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine |
| 2021 | ICRA | What Can I Do Here? Learning New Skills by Imagining Visual Affordances. | Alexander Khazatsky, Ashvin Nair, Daniel Jing, Sergey Levine |
| 2021 | ICRA | Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots. | Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath |
| 2021 | ICRA | DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies. | Soroush Nasiriany, Vitchyr H. Pong, Ashvin Nair, Alexander Khazatsky, Glen Berseth, Sergey Levine |
| 2021 | ICRA | Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models. | Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine |
| 2020 | CoRL | Learning to Walk in the Real World with Minimal Human Effort. | Sehoon Ha, Peng Xu, Zhenyu Tan, Sergey Levine, Jie Tan |
| 2020 | CoRL | Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning. | Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman |
| 2020 | CoRL | Assisted Perception: Optimizing Observations to Communicate State. | Siddharth Reddy, Sergey Levine, Anca D. Dragan |
| 2020 | CoRL | Reinforcement Learning with Videos: Combining Offline Observations with Interaction. | Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn |
| 2020 | CoRL | Chaining Behaviors from Data with Model-Free Reinforcement Learning. | Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine |
| 2020 | CoRL | Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting. | Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart |
| 2020 | CoRL | MELD: Meta-Reinforcement Learning from Images via Latent State Models. | Zihao Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine |
| 2020 | CVPR | RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real. | Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, Mohi Khansari |
| 2020 | ECCV | Learning Predictive Models from Observation and Interaction. | Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn |
| 2020 | ICLR | Adversarial Policies: Attacking Deep Reinforcement Learning. | Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell |
| 2020 | ICLR | The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. | Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine |
| 2020 | ICLR | Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. | Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio |
| 2020 | ICLR | Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery. | Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja, Sergey Levine |
| 2020 | ICLR | 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 |
| 2020 | ICLR | VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation. | Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma |
| 2020 | ICLR | SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards. | Siddharth Reddy, Anca D. Dragan, Sergey Levine |
| 2020 | ICLR | Deep Imitative Models for Flexible Inference, Planning, and Control. | Nicholas Rhinehart, Rowan McAllister, Sergey Levine |
| 2020 | ICLR | Dynamics-Aware Unsupervised Discovery of Skills. | Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman |
| 2020 | ICLR | Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. | Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog |
| 2020 | ICLR | Meta-Learning without Memorization. | Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn |
| 2020 | ICLR | Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards. | Allan Zhou, Eric Jang, Daniel Kappler, Alexander Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn |
| 2020 | ICLR | The Ingredients of Real World Robotic Reinforcement Learning. | Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine |
| 2020 | ICML | Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions. | Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Tom Griffiths, Sergey Levine |
| 2020 | ICML | Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? | Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal |
| 2020 | ICML | Skew-Fit: State-Covering Self-Supervised Reinforcement Learning. | Vitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine |
| 2020 | ICML | Learning Human Objectives by Evaluating Hypothetical Behavior. | Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shane Legg, Jan Leike |
| 2020 | ICML | Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. | Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman |
| 2020 | ICRA | TRASS: Time Reversal as Self-Supervision. | Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, Vikash Kumar |
| 2020 | ICRA | OmniTact: A Multi-Directional High-Resolution Touch Sensor. | Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine |
| 2019 | CoRL | Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning. | Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, Karol Hausman |
| 2019 | CoRL | ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots. | Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar |
| 2019 | CoRL | RoboNet: Large-Scale Multi-Robot Learning. | Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn |
| 2019 | CoRL | Learning Latent Plans from Play. | Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet |
| 2019 | CoRL | Deep Dynamics Models for Learning Dexterous Manipulation. | Anusha Nagabandi, Kurt Konolige, Sergey Levine, Vikash Kumar |
| 2019 | CoRL | Contextual Imagined Goals for Self-Supervised Robotic Learning. | Ashvin Nair, Shikhar Bahl, Alexander Khazatsky, Vitchyr Pong, Glen Berseth, Sergey Levine |
| 2019 | CoRL | Entity Abstraction in Visual Model-Based Reinforcement Learning. | Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine |
| 2019 | CoRL | Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning. | Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine |
| 2019 | CVPR | Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks. | Stephen James, Paul Wohlhart, Mrinal Kalakrishnan, Dmitry Kalashnikov, Alex Irpan, Julian Ibarz, Sergey Levine, Raia Hadsell, Konstantinos Bousmalis |
| 2019 | ICCV | PRECOG: PREdiction Conditioned on Goals in Visual Multi-Agent Settings. | Nicholas Rhinehart, Rowan McAllister, Kris Kitani, Sergey Levine |
| 2019 | ICLR | Automatically Composing Representation Transformations as a Means for Generalization. | Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths |
| 2019 | ICLR | Guiding Policies with Language via Meta-Learning. | John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine |
| 2019 | ICLR | Diversity is All You Need: Learning Skills without a Reward Function. | Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine |
| 2019 | ICLR | From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following. | Justin Fu, Anoop Korattikara, Sergey Levine, Sergio Guadarrama |
| 2019 | ICLR | Learning Actionable Representations with Goal Conditioned Policies. | Dibya Ghosh, Abhishek Gupta, Sergey Levine |
| 2019 | ICLR | Recall Traces: Backtracking Models for Efficient Reinforcement Learning. | Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio |
| 2019 | ICLR | InfoBot: Transfer and Exploration via the Information Bottleneck. | Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine |
| 2019 | ICLR | Unsupervised Learning via Meta-Learning. | Kyle Hsu, Sergey Levine, Chelsea Finn |
| 2019 | ICLR | Reasoning About Physical Interactions with Object-Oriented Prediction and Planning. | Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu |
| 2019 | ICLR | Time-Agnostic Prediction: Predicting Predictable Video Frames. | Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros, Sergey Levine |
| 2019 | ICLR | Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning. | Ilya Kostrikov, Kumar Krishna Agrawal, Debidatta Dwibedi, Sergey Levine, Jonathan Tompson |
| 2019 | ICLR | Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. | Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine |
| 2019 | ICLR | Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning. | Anusha Nagabandi, Ignasi Clavera, Simin Liu, Ronald S. Fearing, Pieter Abbeel, Sergey Levine, Chelsea Finn |
| 2019 | ICLR | Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL. | Anusha Nagabandi, Chelsea Finn, Sergey Levine |
| 2019 | ICLR | Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow. | Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine |
| 2019 | ICML | Online Meta-Learning. | Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine |
| 2019 | ICML | Diagnosing Bottlenecks in Deep Q-learning Algorithms. | Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine |
| 2019 | ICML | EMI: Exploration with Mutual Information. | Hyoungseok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song |
| 2019 | ICML | Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables. | Kate Rakelly, Aurick Zhou, Chelsea Finn, Sergey Levine, Deirdre Quillen |
| 2019 | ICML | Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. | Kelvin Xu, Ellis Ratner, Anca D. Dragan, Sergey Levine, Chelsea Finn |
| 2019 | ICML | SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning. | Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine |
| 2019 | ICRA | Residual Reinforcement Learning for Robot Control. | Tobias Johannink, Shikhar Bahl, Ashvin Nair, Jianlan Luo, Avinash Kumar, Matthias Loskyll, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine |
| 2019 | ICRA | Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight. | Katie Kang, Suneel Belkhale, Gregory Kahn, Pieter Abbeel, Sergey Levine |
| 2019 | ICRA | Data-efficient Learning of Morphology and Controller for a Microrobot. | Thomas Liao, Grant Wang, Brian H. Yang, Rene Lee, Kristofer S. J. Pister, Sergey Levine, Roberto Calandra |
| 2019 | ICRA | Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching. | Justin Lin, Roberto Calandra, Sergey Levine |
| 2019 | ICRA | Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty. | Rowan McAllister, Gregory Kahn, Jeff Clune, Sergey Levine |
| 2018 | CoRL | Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning. | Frederik Ebert, Sudeep Dasari, Alex X. Lee, Sergey Levine, Chelsea Finn |
| 2018 | CoRL | Grasp2Vec: Learning Object Representations from Self-Supervised Grasping. | Eric Jang, Coline Devin, Vincent Vanhoucke, Sergey Levine |
| 2018 | CoRL | Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation. | Gregory Kahn, Adam Villaflor, Pieter Abbeel, Sergey Levine |
| 2018 | CoRL | Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. | Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, Sergey Levine |
| 2018 | CoRL | Few-Shot Goal Inference for Visuomotor Learning and Planning. | Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn |
| 2018 | CVPR | Learning Instance Segmentation by Interaction. | Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik |
| 2018 | CVPR | Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control. | Fereshteh Sadeghi, Alexander Toshev, Eric Jang, Sergey Levine |
| 2018 | ICLR | Stochastic Variational Video Prediction. | Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine |
| 2018 | ICLR | Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. | Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine |
| 2018 | ICLR | Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm. | Chelsea Finn, Sergey Levine |
| 2018 | ICLR | Learning Robust Rewards with Adverserial Inverse Reinforcement Learning. | Justin Fu, Katie Luo, Sergey Levine |
| 2018 | ICLR | Reinforcement Learning from Imperfect Demonstrations. | Yang Gao, Huazhe Xu, Ji Lin, Fisher Yu, Sergey Levine, Trevor Darrell |
| 2018 | ICLR | Divide-and-Conquer Reinforcement Learning. | Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine |
| 2018 | ICLR | Recasting Gradient-Based Meta-Learning as Hierarchical Bayes. | Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas L. Griffiths |
| 2018 | ICLR | Regret Minimization for Partially Observable Deep Reinforcement Learning. | Peter H. Jin, Sergey Levine, Kurt Keutzer |
| 2018 | ICLR | Temporal Difference Models: Model-Free Deep RL for Model-Based Control. | Vitchyr Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine |
| 2018 | ICLR | Conditional Networks for Few-Shot Semantic Segmentation. | Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alyosha A. Efros, Sergey Levine |
| 2018 | ICLR | The Mirage of Action-Dependent Baselines in Reinforcement Learning. | George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine |
| 2018 | ICLR | One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning. | Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine |
| 2018 | ICML | Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. | John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine |
| 2018 | ICML | Latent Space Policies for Hierarchical Reinforcement Learning. | Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, Sergey Levine |
| 2018 | ICML | Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor. | Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine |
| 2018 | ICML | Regret Minimization for Partially Observable Deep Reinforcement Learning. | Peter H. Jin, Kurt Keutzer, Sergey Levine |
| 2018 | ICML | Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control. | Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn |
| 2018 | ICML | The Mirage of Action-Dependent Baselines in Reinforcement Learning. | George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine |
| 2018 | ICRA | Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping. | Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, Yunfei Bai, Matthew Kelcey, Mrinal Kalakrishnan, Laura Downs, Julian Ibarz, Peter Pastor, Kurt Konolige, Sergey Levine, Vincent Vanhoucke |
| 2018 | ICRA | Deep Object-Centric Representations for Generalizable Robot Learning. | Coline Devin, Pieter Abbeel, Trevor Darrell, Sergey Levine |
| 2018 | ICRA | Composable Deep Reinforcement Learning for Robotic Manipulation. | Tuomas Haarnoja, Vitchyr Pong, Aurick Zhou, Murtaza Dalal, Pieter Abbeel, Sergey Levine |
| 2018 | ICRA | Self-Supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation. | Gregory Kahn, Adam Villaflor, Bosen Ding, Pieter Abbeel, Sergey Levine |
| 2018 | ICRA | Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation. | Yuxuan Liu, Abhishek Gupta, Pieter Abbeel, Sergey Levine |
| 2018 | ICRA | Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning. | Anusha Nagabandi, Gregory Kahn, Ronald S. Fearing, Sergey Levine |
| 2018 | ICRA | Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. | Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine |
| 2018 | ICRA | Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-to-End Learning from Demonstration. | Rouhollah Rahmatizadeh, Pooya Abolghasemi, Ladislau Blni, Sergey Levine |
| 2017 | CoRL | The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes? | Roberto Calandra, Andrew Owens, Manu Upadhyaya, Wenzhen Yuan, Justin Lin, Edward H. Adelson, Sergey Levine |
| 2017 | CoRL | Self-Supervised Visual Planning with Temporal Skip Connections. | Frederik Ebert, Chelsea Finn, Alex X. Lee, Sergey Levine |
| 2017 | CoRL | One-Shot Visual Imitation Learning via Meta-Learning. | Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine |
| 2017 | CoRL | End-to-End Learning of Semantic Grasping. | Eric Jang, Sudheendra Vijayanarasimhan, Peter Pastor, Julian Ibarz, Sergey Levine |
| 2017 | CoRL | Learning Robotic Manipulation of Granular Media. | Connor Schenck, Jonathan Tompson, Sergey Levine, Dieter Fox |
| 2017 | CVPR | Cognitive Mapping and Planning for Visual Navigation. | Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, Jitendra Malik |
| 2017 | CVPR | Time-Contrastive Networks: Self-Supervised Learning from Multi-view Observation. | Pierre Sermanet, Corey Lynch, Jasmine Hsu, Sergey Levine |
| 2017 | ICCV | GPLAC: Generalizing Vision-Based Robotic Skills Using Weakly Labeled Images. | Avi Singh, Larry Yang, Sergey Levine |
| 2017 | ICLR | Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning. | Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine |
| 2017 | ICLR | Generalizing Skills with Semi-Supervised Reinforcement Learning. | Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine |
| 2017 | ICLR | Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic. | Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine |
| 2017 | ICLR | Learning Visual Servoing with Deep Features and Fitted Q-Iteration. | Alex X. Lee, Sergey Levine, Pieter Abbeel |
| 2017 | ICLR | EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. | Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran, Sergey Levine |
| 2017 | ICLR | Unsupervised Perceptual Rewards for Imitation Learning. | Pierre Sermanet, Kelvin Xu, Sergey Levine |
| 2017 | ICML | Modular Multitask Reinforcement Learning with Policy Sketches. | Jacob Andreas, Dan Klein, Sergey Levine |
| 2017 | ICML | Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning. | Yevgen Chebotar, Karol Hausman, Marvin Zhang, Gaurav S. Sukhatme, Stefan Schaal, Sergey Levine |
| 2017 | ICML | Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. | Chelsea Finn, Pieter Abbeel, Sergey Levine |
| 2017 | ICML | Reinforcement Learning with Deep Energy-Based Policies. | Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine |
| 2017 | IJCAI | Value Iteration Networks. | Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel |
| 2017 | ICRA | Path integral guided policy search. | Yevgen Chebotar, Mrinal Kalakrishnan, Ali Yahya, Adrian Li, Stefan Schaal, Sergey Levine |
| 2017 | ICRA | Learning modular neural network policies for multi-task and multi-robot transfer. | Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine |
| 2017 | ICRA | Deep visual foresight for planning robot motion. | Chelsea Finn, Sergey Levine |
| 2017 | ICRA | Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates. | Shixiang Gu, Ethan Holly, Timothy P. Lillicrap, Sergey Levine |
| 2017 | ICRA | PLATO: Policy learning using adaptive trajectory optimization. | Gregory Kahn, Tianhao Zhang, Sergey Levine, Pieter Abbeel |
| 2017 | ICRA | Reset-free guided policy search: Efficient deep reinforcement learning with stochastic initial states. | William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine |
| 2017 | ICRA | Combining self-supervised learning and imitation for vision-based rope manipulation. | Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine |
| 2016 | ICML | Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization. | Chelsea Finn, Sergey Levine, Pieter Abbeel |
| 2016 | ICML | Continuous Deep Q-Learning with Model-based Acceleration. | Shixiang Gu, Timothy P. Lillicrap, Ilya Sutskever, Sergey Levine |
| 2016 | ICRA | Deep spatial autoencoders for visuomotor learning. | Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, Pieter Abbeel |
| 2016 | ICRA | Optimal control with learned local models: Application to dexterous manipulation. | Vikash Kumar, Emanuel Todorov, Sergey Levine |
| 2016 | IROS | One-shot learning of manipulation skills with online dynamics adaptation and neural network priors. | Justin Fu, Sergey Levine, Pieter Abbeel |
| 2015 | ICCV | Recurrent Network Models for Human Dynamics. | Katerina Fragkiadaki, Sergey Levine, Panna Felsen, Jitendra Malik |
| 2015 | ICML | Trust Region Policy Optimization. | John Schulman, Sergey Levine, Pieter Abbeel, Michael I. Jordan, Philipp Moritz |
| 2015 | ICRA | Learning force-based manipulation of deformable objects from multiple demonstrations. | Alex X. Lee, Henry Lu, Abhishek Gupta, Sergey Levine, Pieter Abbeel |
| 2015 | ICRA | Learning contact-rich manipulation skills with guided policy search. | Sergey Levine, Nolan Wagener, Pieter Abbeel |
| 2015 | ICRA | Optimism-driven exploration for nonlinear systems. | Teodor Mihai Moldovan, Sergey Levine, Michael I. Jordan, Pieter Abbeel |
| 2014 | ICML | Learning Complex Neural Network Policies with Trajectory Optimization. | Sergey Levine, Vladlen Koltun |
| 2013 | ICML | Guided Policy Search. | Sergey Levine, Vladlen Koltun |
| 2012 | ICML | Continuous Inverse Optimal Control with Locally Optimal Examples. | Sergey Levine, Vladlen Koltun |