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2020 – today
- 2023
[j21]Shagun Sodhani, Sergey Levine, Amy Zhang:
Improving Generalization with Approximate Factored Value Functions. Trans. Mach. Learn. Res. 2023 (2023)- [c358]Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang:
Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. ICLR 2023 - [c357]Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov:
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. ICLR 2023 - [c356]Joey Hong, Aviral Kumar, Sergey Levine:
Confidence-Conditioned Value Functions for Offline Reinforcement Learning. ICLR 2023 - [c355]Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine:
Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes. ICLR 2023 - [c354]Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine:
Efficient Deep Reinforcement Learning Requires Regulating Overfitting. ICLR 2023 - [c353]Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine:
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. ICLR 2023 - [c352]Charlie Snell, Ilya Kostrikov, Yi Su, Sherry Yang, Sergey Levine:
Offline RL for Natural Language Generation with Implicit Language Q Learning. ICLR 2023 - [c351]Philip J. Ball, Laura M. Smith, Ilya Kostrikov, Sergey Levine:
Efficient Online Reinforcement Learning with Offline Data. ICML 2023: 1577-1594 - [c350]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:
PaLM-E: An Embodied Multimodal Language Model. ICML 2023: 8469-8488 - [c349]Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov:
A Connection between One-Step RL and Critic Regularization in Reinforcement Learning. ICML 2023: 9485-9507 - [c348]Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine:
Reinforcement Learning from Passive Data via Latent Intentions. ICML 2023: 11321-11339 - [c347]Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine:
Understanding the Complexity Gains of Single-Task RL with a Curriculum. ICML 2023: 20412-20451 - [c346]Seohong Park, Sergey Levine:
Predictable MDP Abstraction for Unsupervised Model-Based RL. ICML 2023: 27246-27268 - [c345]Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman:
Jump-Start Reinforcement Learning. ICML 2023: 34556-34583 - [c344]Tony Tong Wang, Adam Gleave, Tom Tseng, Kellin Pelrine, Nora Belrose, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell:
Adversarial Policies Beat Superhuman Go AIs. ICML 2023: 35655-35739 - [c343]Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine:
ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation. ICRA 2023: 4077-4084 - [c342]Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman:
Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. ICRA 2023: 5020-5026 - [c341]Kelvin Xu, Zheyuan Hu, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine:
Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance. ICRA 2023: 5938-5945 - [c340]Ashvin Nair, Brian Zhu, Gokul Narayanan, Eugen Solowjow, Sergey Levine:
Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for Industrial Insertion of Novel Connectors from Vision. ICRA 2023: 7154-7161 - [c339]Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, Sergey Levine:
GNM: A General Navigation Model to Drive Any Robot. ICRA 2023: 7226-7233 - [c338]Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. L4DC 2023: 155-169 - [c337]Thomas T. C. K. Zhang, Katie Kang, Bruce D. Lee, Claire J. Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni:
Multi-Task Imitation Learning for Linear Dynamical Systems. L4DC 2023: 586-599 - [c336]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander 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 S. Ryoo, Grecia Salazar, Pannag R. Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-1: Robotics Transformer for Real-World Control at Scale. Robotics: Science and Systems 2023 - [c335]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 Fu, Bob Wei, Sangeetha Ramesh, Khem Holden, Kim Kleiven, David J. Rendleman, Sean Kirmani, Jeffrey Bingham, Jonathan 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:
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. Robotics: Science and Systems 2023 - [c334]Ilya Kostrikov, Laura M. Smith, Sergey Levine:
Demonstrating A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning. Robotics: Science and Systems 2023 - [c333]Aviral Kumar, Anikait Singh, Frederik D. Ebert, Mitsuhiko Nakamoto, Yanlai Yang, Chelsea Finn, Sergey Levine:
Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials. Robotics: Science and Systems 2023 - [c332]Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath:
Robust and Versatile Bipedal Jumping Control through Reinforcement Learning. Robotics: Science and Systems 2023 - [c331]Laura M. Smith, J. Chase Kew, Tianyu Li, Linda Luu, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine:
Learning and Adapting Agile Locomotion Skills by Transferring Experience. Robotics: Science and Systems 2023 - [c330]Ted Xiao, Harris Chan, Pierre Sermanet, Ayzaan Wahid, Anthony Brohan, Karol Hausman, Sergey Levine, Jonathan Tompson:
Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models. Robotics: Science and Systems 2023 - [c329]Tony Z. Zhao, Vikash Kumar, Sergey Levine, Chelsea Finn:
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware. Robotics: Science and Systems 2023 - [i425]Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine:
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. CoRR abs/2302.02931 (2023) - [i424]Philip J. Ball, Laura M. Smith, Ilya Kostrikov, Sergey Levine:
Efficient Online Reinforcement Learning with Offline Data. CoRR abs/2302.02948 (2023) - [i423]Seohong Park, Sergey Levine:
Predictable MDP Abstraction for Unsupervised Model-Based RL. CoRR abs/2302.03921 (2023) - [i422]Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn:
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features. CoRR abs/2302.05441 (2023) - [i421]Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath:
Robust and Versatile Bipedal Jumping Control through Multi-Task Reinforcement Learning. CoRR abs/2302.09450 (2023) - [i420]Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter:
Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control. CoRR abs/2303.00855 (2023) - [i419]Joey Hong, Anca D. Dragan, Sergey Levine:
Learning to Influence Human Behavior with Offline Reinforcement Learning. CoRR abs/2303.02265 (2023) - [i418]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:
PaLM-E: An Embodied Multimodal Language Model. CoRR abs/2303.03378 (2023) - [i417]Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine:
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning. CoRR abs/2303.05479 (2023) - [i416]Manan Tomar, Riashat Islam, Sergey Levine, Philip Bachman:
Ignorance is Bliss: Robust Control via Information Gating. CoRR abs/2303.06121 (2023) - [i415]Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang:
Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. CoRR abs/2303.11373 (2023) - [i414]Dibya Ghosh, Chethan Bhateja, Sergey Levine:
Reinforcement Learning from Passive Data via Latent Intentions. CoRR abs/2304.04782 (2023) - [i413]Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine:
FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing. CoRR abs/2304.09831 (2023) - [i412]Laura M. Smith, J. Chase Kew, Tianyu Li, Linda Luu, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine:
Learning and Adapting Agile Locomotion Skills by Transferring Experience. CoRR abs/2304.09834 (2023) - [i411]Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine:
Efficient Deep Reinforcement Learning Requires Regulating Overfitting. CoRR abs/2304.10466 (2023) - [i410]Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine:
IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies. CoRR abs/2304.10573 (2023) - [i409]Tony Z. Zhao, Vikash Kumar, Sergey Levine, Chelsea Finn:
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware. CoRR abs/2304.13705 (2023) - [i408]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, Jonathan 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:
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. CoRR abs/2305.03270 (2023) - [i407]Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine:
Training Diffusion Models with Reinforcement Learning. CoRR abs/2305.13301 (2023) - [i406]Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song:
The False Promise of Imitating Proprietary LLMs. CoRR abs/2305.15717 (2023) - [i405]Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine:
SACSoN: Scalable Autonomous Data Collection for Social Navigation. CoRR abs/2306.01874 (2023) - [i404]Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine:
Stabilizing Contrastive RL: Techniques for Offline Goal Reaching. CoRR abs/2306.03346 (2023) - [i403]Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn:
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts. CoRR abs/2306.11120 (2023) - [i402]Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine:
ViNT: A Foundation Model for Visual Navigation. CoRR abs/2306.14846 (2023) - [i401]Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine:
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRR abs/2307.00117 (2023) - [i400]Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, Sergey Levine:
Multi-Stage Cable Routing through Hierarchical Imitation Learning. CoRR abs/2307.08927 (2023) - [i399]Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine:
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. CoRR abs/2307.11949 (2023) - [i398]Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov:
A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning. CoRR abs/2307.12968 (2023) - [i397]Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. CoRR abs/2307.13101 (2023) - [i396]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 J. 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 S. Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong T. 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:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRR abs/2307.15818 (2023) - [i395]Homer Walke, Kevin Black, Abraham Lee, Moo Jin Kim, Maximilian Du, Chongyi Zheng, Tony Z. Zhao, Philippe Hansen-Estruch, Quan Vuong, Andre He, Vivek Myers, Kuan Fang, Chelsea Finn, Sergey Levine:
BridgeData V2: A Dataset for Robot Learning at Scale. CoRR abs/2308.12952 (2023) - [i394]Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine:
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. CoRR abs/2309.03322 (2023) - [i393]Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine:
Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning. CoRR abs/2309.03839 (2023) - [i392]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 Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine:
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRR abs/2309.10150 (2023) - [i391]Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar:
Robotic Offline RL from Internet Videos via Value-Function Pre-Training. CoRR abs/2309.13041 (2023) - [i390]Katie Kang, Amrith Setlur, Claire J. Tomlin, Sergey Levine:
Deep Neural Networks Tend To Extrapolate Predictably. CoRR abs/2310.00873 (2023) - [i389]Ajay Sridhar, Dhruv Shah, Catherine Glossop, Sergey Levine:
NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration. CoRR abs/2310.07896 (2023) - [i388]Max Sobol Mark, Archit Sharma, Fahim Tajwar, Rafael Rafailov, Sergey Levine, Chelsea Finn:
Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias. CoRR abs/2310.08558 (2023) - [i387]Seohong Park, Oleh Rybkin, Sergey Levine:
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction. CoRR abs/2310.08887 (2023) - [i386]Han Qi, Xinyang Geng, Stefano Rando, Iku Ohama, Aviral Kumar, Sergey Levine:
Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction. CoRR abs/2310.10056 (2023) - [i385]Dhruv Shah, Michael Equi, Blazej Osinski, Fei Xia, Brian Ichter, Sergey Levine:
Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning. CoRR abs/2310.10103 (2023) - [i384]Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Walke, Chelsea Finn, Aviral Kumar, Sergey Levine:
Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models. CoRR abs/2310.10639 (2023) - [i383]Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine:
Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning. CoRR abs/2310.11731 (2023) - [i382]Laura M. Smith, Yunhao Cao, Sergey Levine:
Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion. CoRR abs/2310.17634 (2023) - [i381]Joey Hong, Anca D. Dragan, Sergey Levine:
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. CoRR abs/2310.20663 (2023) - [i380]Annie S. Chen, Govind Chada, Laura M. Smith, Archit Sharma, Zipeng Fu, Sergey Levine, Chelsea Finn:
Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment. CoRR abs/2311.01059 (2023) - [i379]Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine:
Accelerating Exploration with Unlabeled Prior Data. CoRR abs/2311.05067 (2023) - [i378]Joey Hong, Sergey Levine, Anca D. Dragan:
Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations. CoRR abs/2311.05584 (2023) - [i377]Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine:
RLIF: Interactive Imitation Learning as Reinforcement Learning. CoRR abs/2311.12996 (2023) - 2022
- [j20]Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, Sanja Fidler:
ASE: large-scale reusable adversarial skill embeddings for physically simulated characters. ACM Trans. Graph. 41(4): 94:1-94:17 (2022) - [c328]Dhruv Shah, Arjun Bhorkar, Hrishit Leen, Ilya Kostrikov, Nicholas Rhinehart, Sergey Levine:
Offline Reinforcement Learning for Visual Navigation. CoRL 2022: 44-54 - [c327]Kuan Fang, Patrick Yin, Ashvin Nair, Homer Walke, Gengchen Yan, Sergey Levine:
Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks. CoRL 2022: 106-117 - [c326]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:
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. CoRL 2022: 287-318 - [c325]Dhruv Shah, Blazej Osinski, Brian Ichter, Sergey Levine:
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action. CoRL 2022: 492-504 - [c324]Charles Packer, Nicholas Rhinehart, Rowan Thomas McAllister, Matthew A. Wright, Xin Wang, Jeff He, Sergey Levine, Joseph E. Gonzalez:
Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty. CoRL 2022: 1607-1617 - [c323]Homer Walke, Jonathan Yang, Albert Yu, Aviral Kumar, Jedrzej Orbik, Avi Singh, Sergey Levine:
Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning. CoRL 2022: 1652-1662 - [c322]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:
Inner Monologue: Embodied Reasoning through Planning with Language Models. CoRL 2022: 1769-1782 - [c321]Gilbert Feng, Hongbo Zhang, Zhongyu Li, Xue Bin Peng, Bhuvan Basireddy, Linzhu Yue, Zhitao Song, Lizhi Yang, Yunhui Liu, Koushil Sreenath, Sergey Levine:
GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots. CoRL 2022: 1893-1903 - [c320]Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine:
CoMPS: Continual Meta Policy Search. ICLR 2022 - [c319]Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine:
Information Prioritization through Empowerment in Visual Model-based RL. ICLR 2022 - [c318]Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine:
RvS: What is Essential for Offline RL via Supervised Learning? ICLR 2022 - [c317]Benjamin Eysenbach, Sergey Levine:
Maximum Entropy RL (Provably) Solves Some Robust RL Problems. ICLR 2022 - [c316]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
The Information Geometry of Unsupervised Reinforcement Learning. ICLR 2022 - [c315]Ilya Kostrikov, Ashvin Nair, Sergey Levine:
Offline Reinforcement Learning with Implicit Q-Learning. ICLR 2022 - [c314]Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine:
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. ICLR 2022 - [c313]Aviral Kumar, Joey Hong, Anikait Singh, Sergey Levine:
Should I Run Offline Reinforcement Learning or Behavioral Cloning? ICLR 2022 - [c312]Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine:
Data-Driven Offline Optimization for Architecting Hardware Accelerators. ICLR 2022 - [c311]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:
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 2022 - [c310]Dhruv Shah, Peng Xu, Yao Lu, Ted Xiao, Alexander Toshev, Sergey Levine, Brian Ichter:
Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning. ICLR 2022 - [c309]Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn:
Autonomous Reinforcement Learning: Formalism and Benchmarking. ICLR 2022 - [c308]Mengjiao Yang, Sergey Levine, Ofir Nachum:
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data. ICLR 2022 - [c307]Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez:
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. ICLR 2022 - [c306]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should Be Trained to be Adaptive. ICML 2022: 7513-7530 - [c305]Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine:
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning. ICML 2022: 8407-8426 - [c304]Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine:
Planning with Diffusion for Flexible Behavior Synthesis. ICML 2022: 9902-9915 - [c303]Katie Kang, Paula Gradu, Jason J. Choi, Michael Janner, Claire J. Tomlin, Sergey Levine:
Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control. ICML 2022: 10708-10733 - [c302]Vitchyr H. Pong, Ashvin V. Nair