Sergey Levine - RankMe

1045 papers A* 293A 18C 1Misc 61Journal 588Unranked 83

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AsyncVLA: An Asynchronous VLA for Fast and Robust Navigation on the Edge. CoRR Noriaki Hirose, Catherine Glossop, Dhruv Shah, Sergey Levine
2026	A*	`conf`	Cliqueformer: Model-Based Optimization with Structured Transformers. AAAI Jakub Grudzien Kuba, Pieter Abbeel, Sergey Levine
2026	J	`jnl`	Learning to Drive Anywhere With Model-Based Reannotation. IEEE Robotics Autom. Lett. Noriaki Hirose, Lydia Ignatova, Kyle Stachowicz, Catherine Glossop, Sergey Levine, Dhruv Shah
2026	J	`jnl`	MEM: Multi-Scale Embodied Memory for Vision Language Action Models. CoRR Marcel Torne, Karl Pertsch, Homer Walke, Kyle Vedder, Suraj Nair, Brian Ichter, Allen Z. Ren, Haohuan Wang, Jiaming Tang, Kyle Stachowicz, Karan Dhabalia, Michael Equi, Quan Vuong, Jost Tobias Springenberg, Sergey Levine, Chelsea Finn, Danny Driess
2026	J	`jnl`	Offline Materials Optimization with CliqueFlowmer. CoRR Jakub Grudzien Kuba, Benjamin Kurt Miller, Sergey Levine, Pieter Abbeel
2026	J	`jnl`	Q-learning with Adjoint Matching. CoRR Qiyang Li, Sergey Levine
2026	J	`jnl`	RoboReward: General-Purpose Vision-Language Reward Models for Robotics. CoRR Tony Lee, Andrew Wagenmaker, Karl Pertsch, Percy Liang, Sergey Levine, Chelsea Finn
2026	J	`jnl`	SteerVLA: Steering Vision-Language-Action Models in Long-Tail Driving Scenarios. CoRR Tian Gao, Celine Tan, Catherine Glossop, Timothy Gao, Jiankai Sun, Kyle Stachowicz, Shirley Wu, Oier Mees, Dorsa Sadigh, Sergey Levine, Chelsea Finn
2026	J	`jnl`	Steerable Vision-Language-Action Policies for Embodied Reasoning and Hierarchical Control. CoRR William Chen, Jagdeep Singh Bhatia, Catherine Glossop, Nikhil Mathihalli, Ria Doshi, Andy Tang, Danny Driess, Karl Pertsch, Sergey Levine
2026	J	`jnl`	Traversability-Aware Legged Navigation by Learning From Real-World Visual Data. IEEE Trans. Robotics Hongbo Zhang, Zhongyu Li, Xuanqi Zeng, Laura Smith, Kyle Stachowicz, Dhruv Shah, Linzhu Yue, Zhitao Song, Weipeng Xia, Sergey Levine, Koushil Sreenath, Yun-Hui Liu
2025	J	`jnl`	A Stable Whitening Optimizer for Efficient Neural Network Training. CoRR Kevin Frans, Sergey Levine, Pieter Abbeel
2025	A*	`conf`	Adding Conditional Control to Diffusion Models with Reinforcement Learning. ICLR Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Sun-Yuan Kung, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali
2025	J	`jnl`	AutoEval: Autonomous Evaluation of Generalist Robot Manipulation Policies in the Real World. CoRR Zhiyuan Zhou, Pranav Atreya, You Liang Tan, Karl Pertsch, Sergey Levine
2025	A*	`conf`	Behavioral Exploration: Learning to Explore via In-Context Adaptation. ICML Andrew Wagenmaker, Zhiyuan Zhou, Sergey Levine
2025	J	`jnl`	Behavioral Exploration: Learning to Explore via In-Context Adaptation. CoRR Andrew Wagenmaker, Zhiyuan Zhou, Sergey Levine
2025	A*	`conf`	Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding. ICRA Joshua Jones, Oier Mees, Carmelo Sferrazza, Kyle Stachowicz, Pieter Abbeel, Sergey Levine
2025	J	`jnl`	Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding. CoRR Joshua Jones, Oier Mees, Carmelo Sferrazza, Kyle Stachowicz, Pieter Abbeel, Sergey Levine
2025	J	`jnl`	CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models. CoRR Catherine Glossop, William Chen, Arjun Bhorkar, Dhruv Shah, Sergey Levine
2025	A*	`conf`	Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models. ICRA Annie S. Chen, Alec M. Lessing, Andy Tang, Govind Chada, Laura Smith, Sergey Levine, Chelsea Finn
2025	J	`jnl`	Compute-Optimal Scaling for Value-Based Deep RL. CoRR Preston Fu, Oleh Rybkin, Zhiyuan Zhou, Michal Nauman, Pieter Abbeel, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Consistently Simulating Human Personas with Multi-Turn Reinforcement Learning. CoRR Marwa Abdulhai, Ryan Cheng, Donovan Clay, Tim Althoff, Sergey Levine, Natasha Jaques
2025	J	`jnl`	Decoupled Q-Chunking. CoRR Qiyang Li, Seohong Park, Sergey Levine
2025	J	`jnl`	Diffusion Guidance Is a Controllable Policy Improvement Operator. CoRR Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine
2025	J	`jnl`	Digi-Q: Learning Q-Value Functions for Training Device-Control Agents. CoRR Hao Bai, Yifei Zhou, Li Erran Li, Sergey Levine, Aviral Kumar
2025	A*	`conf`	Digi-Q: Learning VLM Q-Value Functions for Training Device-Control Agents. ICLR Hao Bai, Yifei Zhou, Li Erran Li, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Dual Goal Representations. CoRR Seohong Park, Deepinder Mann, Sergey Levine
2025	J	`jnl`	Dynamic Search for Inference-Time Alignment in Diffusion Models. CoRR Xiner Li, Masatoshi Uehara, Xingyu Su, Gabriele Scalia, Tommaso Biancalani, Aviv Regev, Sergey Levine, Shuiwang Ji
2025	A*	`conf`	Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data. ICLR Zhiyuan Zhou, Andy Peng, Qiyang Li, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Emergence of Human to Robot Transfer in Vision-Language-Action Models. CoRR Simar Kareer, Karl Pertsch, James Darpinian, Judy Hoffman, Danfei Xu, Sergey Levine, Chelsea Finn, Suraj Nair
2025	J	`jnl`	Evaluating & Reducing Deceptive Dialogue From Language Models with Multi-turn RL. CoRR Marwa Abdulhai, Ryan Cheng, Aryansh Shrivastava, Natasha Jaques, Yarin Gal, Sergey Levine
2025	J	`jnl`	FAST: Efficient Action Tokenization for Vision-Language-Action Models. CoRR Karl Pertsch, Kyle Stachowicz, Brian Ichter, Danny Driess, Suraj Nair, Quan Vuong, Oier Mees, Chelsea Finn, Sergey Levine
2025	J	`jnl`	FMB: A functional manipulation benchmark for generalizable robotic learning. Int. J. Robotics Res. Jianlan Luo, Charles Xu, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine
2025	A*	`conf`	Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design. ICLR Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Aviv Regev, Hanchen Wang, Tommaso Biancalani
2025	A*	`conf`	Flow Q-Learning. ICML Seohong Park, Qiyang Li, Sergey Levine
2025	J	`jnl`	Flow Q-Learning. CoRR Seohong Park, Qiyang Li, Sergey Levine
2025	A*	`conf`	GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. ICRA Kyle Beltran Hatch, Ashwin Balakrishna, Oier Mees, Suraj Nair, Seohong Park, Blake Wulfe, Masha Itkina, Benjamin Eysenbach, Sergey Levine, Thomas Kollar, Benjamin Burchfiel
2025	A*	`conf`	Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models. ICML 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	J	`jnl`	Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models. CoRR Lucy Xiaoyang Shi, Brian Ichter, Michael 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	J	`jnl`	Horizon Reduction Makes RL Scalable. CoRR Seohong Park, Kevin Frans, Deepinder Mann, Benjamin Eysenbach, Aviral Kumar, Sergey Levine
2025	J	`jnl`	Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review. CoRR Masatoshi Uehara, Yulai Zhao, Chenyu Wang, Xiner Li, Aviv Regev, Sergey Levine, Tommaso Biancalani
2025	J	`jnl`	Intention-Conditioned Flow Occupancy Models. CoRR Chongyi Zheng, Seohong Park, Sergey Levine, Benjamin Eysenbach
2025	A*	`conf`	KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation Without Robot Data. ICRA Grace Tang, Swetha Rajkumar, Yifei Zhou, Homer Rich Walke, Sergey Levine, Kuan Fang
2025	J	`jnl`	Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better. CoRR Danny Driess, Jost Tobias Springenberg, Brian Ichter, Lili Yu, Adrian Li-Bell, Karl Pertsch, Allen Z. Ren, Homer Walke, Quan Vuong, Lucy Xiaoyang Shi, Sergey Levine
2025	A*	`conf`	LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models. ICML Marwa Abdulhai, Isadora White, Charlie Victor Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine
2025	A*	`conf`	Language Guided Skill Discovery. ICLR Seungeun Rho, Laura Smith, Tianyu Li, Sergey Levine, Xue Bin Peng, Sehoon Ha
2025	J	`jnl`	Learning Affordances at Inference-Time for Vision-Language-Action Models. CoRR Ameesh Shah, William Chen, Adwait Godbole, Federico Mora, Sanjit A. Seshia, Sergey Levine
2025	A*	`conf`	Learning Visuotactile Skills With Two Multifingered Hands. ICRA Toru Lin, Yu Zhang, Qiyang Li, Haozhi Qi, Brent Yi, Sergey Levine, Jitendra Malik
2025	J	`jnl`	Learning to Drive Anywhere with Model-Based Reannotation. CoRR Noriaki Hirose, Lydia Ignatova, Kyle Stachowicz, Catherine Glossop, Sergey Levine, Dhruv Shah
2025	J	`jnl`	Learning to Reason without External Rewards. CoRR Xuandong Zhao, Zhewei Kang, Aosong Feng, Sergey Levine, Dawn Song
2025	J	`jnl`	Leveraging Discrete Function Decomposability for Scientific Design. CoRR James C. Bowden, Sergey Levine, Jennifer Listgarten
2025	A*	`conf`	Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration. ICML Max Wilcoxson, Qiyang Li, Kevin Frans, Sergey Levine
2025	J	`jnl`	Multistep Quasimetric Learning for Scalable Goal-conditioned Reinforcement Learning. CoRR Bill Chunyuan Zheng, Vivek Myers, Benjamin Eysenbach, Sergey Levine
2025	J	`jnl`	Natural Language Actor-Critic: Scalable Off-Policy Learning in Language Space. CoRR Joey Hong, Kang Liu, Zhan Ling, Jiecao Chen, Sergey Levine
2025	A*	`conf`	OGBench: Benchmarking Offline Goal-Conditioned RL. ICLR Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine
2025	J	`jnl`	Offline Goal-conditioned Reinforcement Learning with Quasimetric Representations. CoRR Vivek Myers, Bill Chunyuan Zheng, Benjamin Eysenbach, Sergey Levine
2025	J	`jnl`	OmniVLA: An Omni-Modal Vision-Language-Action Model for Robot Navigation. CoRR Noriaki Hirose, Catherine Glossop, Dhruv Shah, Sergey Levine
2025	A*	`conf`	One Step Diffusion via Shortcut Models. ICLR Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel
2025	J	`jnl`	Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL. CoRR Joey Hong, Anca D. Dragan, Sergey Levine
2025	J	`jnl`	PolaRiS: Scalable Real-to-Sim Evaluations for Generalist Robot Policies. CoRR Arhan Jain, Mingtong Zhang, Kanav Arora, William Chen, Marcel Torne, Muhammad Zubair Irshad, Sergey Zakharov, Yue Wang, Sergey Levine, Chelsea Finn, Wei-Chiu Ma, Dhruv Shah, Abhishek Gupta, Karl Pertsch
2025	J	`jnl`	Posterior Behavioral Cloning: Pretraining BC Policies for Efficient RL Finetuning. CoRR Andrew Wagenmaker, Perry Dong, Raymond Tsao, Chelsea Finn, Sergey Levine
2025	J	`jnl`	Precise and dexterous robotic manipulation via human-in-the-loop reinforcement learning. Sci. Robotics Jianlan Luo, Charles Xu, Jeffrey Wu, Sergey Levine
2025	A*	`conf`	Prioritized Generative Replay. ICLR Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine, Alexei A. Efros
2025	A*	`conf`	Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents. ICML Yifei Zhou, Qianlan Yang, Kaixiang Lin, Min Bai, Xiong Zhou, Yu-Xiong Wang, Sergey Levine, Li Erran Li
2025	A*	`conf`	Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning. ICLR Joey Hong, Anca D. Dragan, Sergey Levine
2025	J	`jnl`	RLAC: Reinforcement Learning with Adversarial Critic for Free-Form Generation Tasks. CoRR Mian Wu, Gavin Zhang, Sewon Min, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Real-Time Execution of Action Chunking Flow Policies. CoRR Kevin Black, Manuel Y. Galliker, Sergey Levine
2025	J	`jnl`	Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation. CoRR Yunhai Feng, Jiaming Han, Zhuoran Yang, Xiangyu Yue, Sergey Levine, Jianlan Luo
2025	J	`jnl`	Reinforcement Learning with Action Chunking. CoRR Qiyang Li, Zhiyuan Zhou, Sergey Levine
2025	J	`jnl`	Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control. Int. J. Robotics Res. Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath
2025	A*	`conf`	Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design. ICML Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani
2025	J	`jnl`	Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design. CoRR Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani
2025	J	`jnl`	RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies. CoRR Pranav Atreya, Karl Pertsch, Tony Lee, Moo Jin Kim, Arhan Jain, Artur Kuramshin, Clemens Eppner, Cyrus Neary, Edward S. Hu, Fabio Ramos, Jonathan Tremblay, Kanav Arora, Kirsty Ellis, Luca Macesanu, Matthew Leonard, Meedeum Cho, Ozgur Aslan, Shivin Dass, Jie Wang, Xingfang Yuan, Xuning Yang, Abhishek Gupta, Dinesh Jayaraman, Glen Berseth, Kostas Daniilidis, Roberto Martin Martin, Youngwoon Lee, Percy Liang, Chelsea Finn, Sergey Levine
2025	J	`jnl`	Robust Finetuning of Vision-Language-Action Robot Policies via Parameter Merging. CoRR Yajat Yadav, Zhiyuan Zhou, Andrew Wagenmaker, Karl Pertsch, Sergey Levine
2025	A*	`conf`	SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training. ICML Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V. Le, Sergey Levine, Yi Ma
2025	J	`jnl`	SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training. CoRR Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V. Le, Sergey Levine, Yi Ma
2025	J	`jnl`	SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks. CoRR Yifei Zhou, Song Jiang, Yuandong Tian, Jason Weston, Sergey Levine, Sainbayar Sukhbaatar, Xian Li
2025	J	`jnl`	Scalable Offline Model-Based RL with Action Chunks. CoRR Kwanyoung Park, Seohong Park, Youngwoon Lee, Sergey Levine
2025	A*	`conf`	Scaling Test-Time Compute Without Verification or RL is Suboptimal. ICML Amrith Setlur, Nived Rajaraman, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Scaling Test-Time Compute Without Verification or RL is Suboptimal. CoRR Amrith Setlur, Nived Rajaraman, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Self-Challenging Language Model Agents. CoRR Yifei Zhou, Sergey Levine, Jason Weston, Xian Li, Sainbayar Sukhbaatar
2025	J	`jnl`	Steering Your Diffusion Policy with Latent Space Reinforcement Learning. CoRR Andrew Wagenmaker, Mitsuhiko Nakamoto, Yunchu Zhang, Seohong Park, Waleed Yagoub, Anusha Nagabandi, Abhishek Gupta, Sergey Levine
2025	J	`jnl`	Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following. CoRR Vivek Myers, Bill Chunyuan Zheng, Anca D. Dragan, Kuan Fang, Sergey Levine
2025	A*	`conf`	The Ingredients for Robotic Diffusion Transformers. ICRA Sudeep Dasari, Oier Mees, Sebastian Zhao, Mohan Kumar Srirama, Sergey Levine
2025	J	`jnl`	Training LLM Agents to Empower Humans. CoRR Evan Ellis, Vivek Myers, Jens Tuyls, Sergey Levine, Anca D. Dragan, Benjamin Eysenbach
2025	J	`jnl`	Training Strategies for Efficient Embodied Reasoning. CoRR William Chen, Suneel Belkhale, Suvir Mirchandani, Oier Mees, Danny Driess, Karl Pertsch, Sergey Levine
2025	J	`jnl`	Training-Time Action Conditioning for Efficient Real-Time Chunking. CoRR Kevin Black, Allen Z. Ren, Michael Equi, Sergey Levine
2025	J	`jnl`	Transitive RL: Value Learning via Divide and Conquer. CoRR Seohong Park, Aditya Oberai, Pranav Atreya, Sergey Levine
2025	—	`conf`	Unfamiliar Finetuning Examples Control How Language Models Hallucinate. NAACL (Long Papers) Katie Kang, Eric Wallace, Claire J. Tomlin, Aviral Kumar, Sergey Levine
2025	A*	`conf`	Value-Based Deep RL Scales Predictably. ICML Oleh Rybkin, Michal Nauman, Preston Fu, Charlie Victor Snell, Pieter Abbeel, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Value-Based Deep RL Scales Predictably. CoRR Oleh Rybkin, Michal Nauman, Preston Fu, Charlie Snell, Pieter Abbeel, Sergey Levine, Aviral Kumar
2025	J	`jnl`	ViVa: Video-Trained Value Functions for Guiding Online RL from Diverse Data. CoRR Nitish Dashora, Dibya Ghosh, Sergey Levine
2025	J	`jnl`	Vision-Language Models Provide Promptable Representations for Reinforcement Learning. Trans. Mach. Learn. Res. William Chen, Oier Mees, Aviral Kumar, Sergey Levine
2025	J	`jnl`	Visual Pre-Training on Unlabeled Images using Reinforcement Learning. CoRR Dibya Ghosh, Sergey Levine
2025	A*	`conf`	What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning? ICML Katie Kang, Amrith Setlur, Dibya Ghosh, Jacob Steinhardt, Claire J. Tomlin, Sergey Levine, Aviral Kumar
2025	J	`jnl`	What Really Matters in Matrix-Whitening Optimizers? CoRR Kevin Frans, Pieter Abbeel, Sergey Levine
2025	J	`jnl`	Zero-Overhead Introspection for Adaptive Test-Time Compute. CoRR Rohin Manvi, Joey Hong, Tim Seyde, Maxime Labonne, Mathias Lechner, Sergey Levine
2025	J	`jnl`	π CoRR Physical Intelligence, Kevin Black, Noah Brown, James Darpinian, Karan Dhabalia, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Manuel Y. Galliker, Dibya Ghosh, Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, Liyiming Ke, Devin LeBlanc, Sergey Levine, Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Allen Z. Ren, Lucy Xiaoyang Shi, Laura Smith, Jost Tobias Springenberg, Kyle Stachowicz, James Tanner, Quan Vuong, Homer Walke, Anna Walling, Haohuan Wang, Lili Yu, Ury Zhilinsky
2025	J	`jnl`	π CoRR Physical Intelligence, Ali Amin, Raichelle Aniceto, Ashwin Balakrishna, Kevin Black, Ken Conley, Grace Connors, James Darpinian, Karan Dhabalia, Jared DiCarlo, Danny Driess, Michael Equi, Adnan Esmail, Yunhao Fang, Chelsea Finn, Catherine Glossop, Thomas Godden, Ivan Goryachev, Lachy Groom, Hunter Hancock, Karol Hausman, Gashon Hussein, Brian Ichter, Szymon Jakubczak, Rowan Jen, Tim Jones, Ben Katz, Liyiming Ke, Chandra Kuchi, Marinda Lamb, Devin LeBlanc, Sergey Levine, Adrian Li-Bell, Yao Lu, Vishnu Mano, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Allen Z. Ren, Charvi Sharma, Lucy Xiaoyang Shi, Laura Smith, Jost Tobias Springenberg, Kyle Stachowicz, Will Stoeckle, Alex Swerdlow, James Tanner, Marcel Torne, Quan Vuong, Anna Walling, Haohuan Wang, Blake Williams, Sukwon Yoo, Lili Yu, Ury Zhilinsky, Zhiyuan Zhou
2024	J	`jnl`	Adding Conditional Control to Diffusion Models with Reinforcement Learning. CoRR Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali
2024	A*	`conf`	ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL. ICML Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar
2024	J	`jnl`	ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL. CoRR Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar
2024	J	`jnl`	AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents. CoRR Michael Ahn, Debidatta Dwibedi, Chelsea Finn, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Karol Hausman, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Sean Kirmani, Isabel Leal, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Sharath Maddineni, Kanishka Rao, Dorsa Sadigh, Pannag Sanketi, Pierre Sermanet, Quan Vuong, Stefan Welker, Fei Xia, Ted Xiao, Peng Xu, Steve Xu, Zhuo Xu
2024	J	`jnl`	Autonomous Evaluation and Refinement of Digital Agents. CoRR Jiayi Pan, Yichi Zhang, Nicholas Tomlin, Yifei Zhou, Sergey Levine, Alane Suhr
2024	Misc	`conf`	Autonomous Improvement of Instruction Following Skills via Foundation Models. CoRL Zhiyuan Zhou, Pranav Atreya, Abraham Lee, Homer Rich Walke, Oier Mees, Sergey Levine
2024	J	`jnl`	Autonomous Improvement of Instruction Following Skills via Foundation Models. CoRR Zhiyuan Zhou, Pranav Atreya, Abraham Lee, Homer Walke, Oier Mees, Sergey Levine
2024	A*	`conf`	Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models. NeurIPS Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani
2024	J	`jnl`	Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models. CoRR Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani
2024	A*	`conf`	Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. ICML Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter
2024	J	`jnl`	Cliqueformer: Model-Based Optimization with Structured Transformers. CoRR Jakub Grudzien Kuba, Pieter Abbeel, Sergey Levine
2024	J	`jnl`	Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models. CoRR Annie S. Chen, Alec M. Lessing, Andy Tang, Govind Chada, Laura Smith, Sergey Levine, Chelsea Finn
2024	J	`jnl`	D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. RLJ Rafael Rafailov, Kyle Beltran Hatch, Anikait Singh, Aviral Kumar, Laura Smith, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Sergey Levine, Chelsea Finn
2024	J	`jnl`	D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. CoRR Rafael Rafailov, Kyle Hatch, Anikait Singh, Laura Smith, Aviral Kumar, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Chelsea Finn, Sergey Levine
2024	—	`conf`	DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. Robotics: Science and Systems Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Yecheng Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R. Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, Jensen Gao, David Antonio Herrera, Minho Heo, Kyle Hsu, Jiaheng Hu, Donovon Jackson, Charlotte Le, Yunshuang Li, Roy Lin, Zehan Ma, Abhiram Maddukuri, Suvir Mirchandani, Daniel Morton, Tony Nguyen, Abigail O'Neill, Rosario Scalise, Derick Seale, Victor Son, Stephen Tian, Emi Tran, Andrew E. Wang, Yilin Wu, Annie Xie, Jingyun Yang, Patrick Yin, Yunchu Zhang, Osbert Bastani, Glen Berseth, Jeannette Bohg, Ken Goldberg, Abhinav Gupta, Abhishek Gupta, Dinesh Jayaraman, Joseph J. Lim, Jitendra Malik, Roberto Martín-Martín, Subramanian Ramamoorthy, Dorsa Sadigh, Shuran Song, Jiajun Wu, Michael C. Yip, Yuke Zhu, Thomas Kollar, Sergey Levine, Chelsea Finn
2024	A*	`conf`	Deep Neural Networks Tend To Extrapolate Predictably. ICLR Katie Kang, Amrith Setlur, Claire J. Tomlin, Sergey Levine
2024	A	`conf`	Defining Deception in Decision Making. AAMAS Marwa Abdulhai, Micah Carroll, Justin Svegliato, Anca D. Dragan, Sergey Levine
2024	J	`jnl`	Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding. CoRR Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Aviv Regev, Sergey Levine, Masatoshi Uehara
2024	A*	`conf`	Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization. NeurIPS Aniketh Janardhan Reddy, Xinyang Geng, Michael Herschl, Sathvik Kolli, Aviral Kumar, Patrick Hsu, Sergey Levine, Nilah Ioannidis
2024	A*	`conf`	DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning. NeurIPS Hao Bai, Yifei Zhou, Jiayi Pan, Mert Cemri, Alane Suhr, Sergey Levine, Aviral Kumar
2024	J	`jnl`	DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning. CoRR Hao Bai, Yifei Zhou, Mert Cemri, Jiayi Pan, Alane Suhr, Sergey Levine, Aviral Kumar
2024	J	`jnl`	Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data. CoRR Zhiyuan Zhou, Andy Peng, Qiyang Li, Sergey Levine, Aviral Kumar
2024	Misc	`conf`	Evaluating Real-World Robot Manipulation Policies in Simulation. CoRL 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	J	`jnl`	Evaluating Real-World Robot Manipulation Policies in Simulation. CoRR Xuanlin Li, Kyle Hsu, Jiayuan Gu, Karl Pertsch, Oier Mees, Homer Rich Walke, Chuyuan Fu, Ishikaa Lunawat, Isabel Sieh, Sean Kirmani, Sergey Levine, Jiajun Wu, Chelsea Finn, Hao Su, Quan Vuong, Ted Xiao
2024	J	`jnl`	FMB: a Functional Manipulation Benchmark for Generalizable Robotic Learning. CoRR Jianlan Luo, Charles Xu, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine
2024	A*	`conf`	Feedback Efficient Online Fine-Tuning of Diffusion Models. ICML Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani
2024	J	`jnl`	Feedback Efficient Online Fine-Tuning of Diffusion Models. CoRR Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani
2024	J	`jnl`	Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design. CoRR Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Hanchen Wang, Aviv Regev
2024	A*	`conf`	Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. NeurIPS Simon Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Peter Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine
2024	J	`jnl`	Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. CoRR Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine
2024	J	`jnl`	Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control. CoRR Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Tommaso Biancalani, Sergey Levine
2024	A*	`conf`	Foundation Policies with Hilbert Representations. ICML Seohong Park, Tobias Kreiman, Sergey Levine
2024	J	`jnl`	Foundation Policies with Hilbert Representations. CoRR Seohong Park, Tobias Kreiman, Sergey Levine
2024	A	`conf`	Functional Graphical Models: Structure Enables Offline Data-Driven Optimization. AISTATS Kuba Grudzien Kuba, Masatoshi Uehara, Sergey Levine, Pieter Abbeel
2024	J	`jnl`	Functional Graphical Models: Structure Enables Offline Data-Driven Optimization. CoRR Jakub Grudzien Kuba, Masatoshi Uehara, Pieter Abbeel, Sergey Levine
2024	J	`jnl`	GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. CoRR Kyle Beltran Hatch, Ashwin Balakrishna, Oier Mees, Suraj Nair, Seohong Park, Blake Wulfe, Masha Itkina, Benjamin Eysenbach, Sergey Levine, Thomas Kollar, Benjamin Burchfiel
2024	A*	`conf`	Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion. ICRA Laura Smith, Yunhao Cao, Sergey Levine
2024	A	`conf`	HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation. IROS Xiaoyu Huang, Qiayuan Liao, Yiming Ni, Zhongyu Li, Laura Smith, Sergey Levine, Xue Bin Peng, Koushil Sreenath
2024	J	`jnl`	HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation. CoRR Xiaoyu Huang, Qiayuan Liao, Yiming Ni, Zhongyu Li, Laura Smith, Sergey Levine, Xue Bin Peng, Koushil Sreenath
2024	A*	`conf`	Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. NeurIPS Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine
2024	J	`jnl`	Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. CoRR Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine
2024	J	`jnl`	Interactive Dialogue Agents via Reinforcement Learning on Hindsight Regenerations. CoRR Joey Hong, Jessica Lin, Anca D. Dragan, Sergey Levine
2024	A*	`conf`	Is Value Learning Really the Main Bottleneck in Offline RL? NeurIPS Seohong Park, Kevin Frans, Sergey Levine, Aviral Kumar
2024	J	`jnl`	Is Value Learning Really the Main Bottleneck in Offline RL? CoRR Seohong Park, Kevin Frans, Sergey Levine, Aviral Kumar
2024	J	`jnl`	KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data. CoRR Grace Tang, Swetha Rajkumar, Yifei Zhou, Homer Rich Walke, Sergey Levine, Kuan Fang
2024	J	`jnl`	Language Guided Skill Discovery. CoRR Seungeun Rho, Laura Smith, Tianyu Li, Sergey Levine, Xue Bin Peng, Sehoon Ha
2024	Misc	`conf`	LeLaN: Learning A Language-Conditioned Navigation Policy from In-the-Wild Video. CoRL Noriaki Hirose, Catherine Glossop, Ajay Sridhar, Oier Mees, Sergey Levine
2024	J	`jnl`	LeLaN: Learning A Language-Conditioned Navigation Policy from In-the-Wild Videos. CoRR Noriaki Hirose, Catherine Glossop, Ajay Sridhar, Dhruv Shah, Oier Mees, Sergey Levine
2024	A*	`conf`	Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. ICML Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach
2024	J	`jnl`	Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. CoRR Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach
2024	J	`jnl`	Learning Visuotactile Skills with Two Multifingered Hands. CoRR Toru Lin, Yu Zhang, Qiyang Li, Haozhi Qi, Brent Yi, Sergey Levine, Jitendra Malik
2024	A*	`conf`	Learning to Assist Humans without Inferring Rewards. NeurIPS Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca D. Dragan
2024	J	`jnl`	Learning to Assist Humans without Inferring Rewards. CoRR Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca D. Dragan
2024	A*	`conf`	Learning to Explore in POMDPs with Informational Rewards. ICML Annie Xie, Logan M. Bhamidipaty, Evan Zheran Liu, Joey Hong, Sergey Levine, Chelsea Finn
2024	J	`jnl`	Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration. CoRR Max Wilcoxson, Qiyang Li, Kevin Frans, Sergey Levine
2024	Misc	`conf`	Lifelong Autonomous Improvement of Navigation Foundation Models in the Wild. CoRL Kyle Stachowicz, Lydia Ignatova, Sergey Levine
2024	A*	`conf`	METRA: Scalable Unsupervised RL with Metric-Aware Abstraction. ICLR Seohong Park, Oleh Rybkin, Sergey Levine
2024	J	`jnl`	MOKA: Open-Vocabulary Robotic Manipulation through Mark-Based Visual Prompting. CoRR Fangchen Liu, Kuan Fang, Pieter Abbeel, Sergey Levine
2024	—	`conf`	MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting. Robotics: Science and Systems Kuan Fang, Fangchen Liu, Pieter Abbeel, Sergey Levine
2024	Misc	`conf`	Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. CoRL 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	J	`jnl`	Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. CoRR Hao-Tien Lewis Chiang, Zhuo Xu, 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	J	`jnl`	Multistage Cable Routing Through Hierarchical Imitation Learning. IEEE Trans. Robotics Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, Sergey Levine
2024	A*	`conf`	NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration. ICRA Ajay Sridhar, Dhruv Shah, Catherine Glossop, Sergey Levine
2024	J	`jnl`	OGBench: Benchmarking Offline Goal-Conditioned RL. CoRR Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine
2024	—	`conf`	Octo: An Open-Source Generalist Robot Policy. Robotics: Science and Systems Dibya Ghosh, Homer Rich Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Quan Vuong, Ted Xiao, Pannag R. Sanketi, Dorsa Sadigh, Chelsea Finn, Sergey Levine
2024	J	`jnl`	Octo: An Open-Source Generalist Robot Policy. CoRR Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Pannag Sanketi, Quan Vuong, Ted Xiao, Dorsa Sadigh, Chelsea Finn, Sergey Levine
2024	A*	`conf`	Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. ICLR Joey Hong, Anca D. Dragan, Sergey Levine
2024	J	`jnl`	One Step Diffusion via Shortcut Models. CoRR Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel
2024	A*	`conf`	Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 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 Schölkopf, 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 Büchler, 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, João Silvério, 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 Sünderhauf, 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 Martín-Martín, 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
2024	Misc	`conf`	OpenVLA: An Open-Source Vision-Language-Action Model. CoRL 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	J	`jnl`	OpenVLA: An Open-Source Vision-Language-Action Model. CoRR Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Paul Foster, Grace Lam, Pannag Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, Chelsea Finn
2024	A*	`conf`	PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. ICML 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	J	`jnl`	PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. CoRR 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	Misc	`conf`	Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation. CoRL Vivek Myers, Chunyuan Zheng, Oier Mees, Kuan Fang, Sergey Levine
2024	J	`jnl`	Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation. CoRR Vivek Myers, Bill Chunyuan Zheng, Oier Mees, Sergey Levine, Kuan Fang
2024	J	`jnl`	Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning. CoRR Jianlan Luo, Charles Xu, Jeffrey Wu, Sergey Levine
2024	J	`jnl`	Predicting Emergent Capabilities by Finetuning. CoRR Charlie Snell, Eric Wallace, Dan Klein, Sergey Levine
2024	J	`jnl`	Prioritized Generative Replay. CoRR Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine, Alexei A. Efros
2024	A*	`conf`	Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features. ICLR Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn
2024	A*	`conf`	Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models. ICML Amrith Setlur, Saurabh Garg, Virginia Smith, Sergey Levine
2024	J	`jnl`	Proposer-Agent-Evaluator(PAE): Autonomous Skill Discovery For Foundation Model Internet Agents. CoRR Yifei Zhou, Qianlan Yang, Kaixiang Lin, Min Bai, Xiong Zhou, Yu-Xiong Wang, Sergey Levine, Li Erran Li
2024	—	`conf`	Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation. Robotics: Science and Systems Jonathan Heewon Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah, Quan Vuong, Chelsea Finn, Dorsa Sadigh, Sergey Levine
2024	J	`jnl`	Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation. CoRR Jonathan Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah, Quan Vuong, Chelsea Finn, Dorsa Sadigh, Sergey Levine
2024	J	`jnl`	Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning. CoRR Joey Hong, Anca D. Dragan, Sergey Levine
2024	—	`conf`	RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes. Robotics: Science and Systems Kyle Stachowicz, Sergey Levine
2024	J	`jnl`	RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes. CoRR Kyle Stachowicz, Sergey Levine
2024	J	`jnl`	RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning. CoRR Charles Xu, Qiyang Li, Jianlan Luo, Sergey Levine
2024	A*	`conf`	RLIF: Interactive Imitation Learning as Reinforcement Learning. ICLR Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine
2024	J	`jnl`	Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control. CoRR Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath
2024	Misc	`conf`	Robotic Control via Embodied Chain-of-Thought Reasoning. CoRL Michal Zawalski, William Chen, Karl Pertsch, Oier Mees, Chelsea Finn, Sergey Levine
2024	J	`jnl`	Robotic Control via Embodied Chain-of-Thought Reasoning. CoRR Michal Zawalski, William Chen, Karl Pertsch, Oier Mees, Chelsea Finn, Sergey Levine
2024	A*	`conf`	Robotic Offline RL from Internet Videos via Value-Function Learning. ICRA Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar
2024	J	`jnl`	SACSoN: Scalable Autonomous Control for Social Navigation. IEEE Robotics Autom. Lett. Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine
2024	Misc	`conf`	SELFI: Autonomous Self-Improvement with RL for Vision-Based Navigation around People. CoRL Noriaki Hirose, Dhruv Shah, Kyle Stachowicz, Ajay Sridhar, Sergey Levine
2024	J	`jnl`	SELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation. CoRR Noriaki Hirose, Dhruv Shah, Kyle Stachowicz, Ajay Sridhar, Sergey Levine
2024	A*	`conf`	SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. ICRA Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine
2024	J	`jnl`	SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. CoRR Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine
2024	Misc	`conf`	Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation. CoRL Ria Doshi, Homer Rich Walke, Oier Mees, Sudeep Dasari, Sergey Levine
2024	J	`jnl`	Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation. CoRR Ria Doshi, Homer Walke, Oier Mees, Sudeep Dasari, Sergey Levine
2024	A*	`conf`	Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data. ICLR Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine
2024	Misc	`conf`	Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance. CoRL Mitsuhiko Nakamoto, Oier Mees, Aviral Kumar, Sergey Levine
2024	J	`jnl`	Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance. CoRR Mitsuhiko Nakamoto, Oier Mees, Aviral Kumar, Sergey Levine
2024	A*	`conf`	Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. ICML 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
2024	J	`jnl`	Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. CoRR 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
2024	J	`jnl`	Strategically Conservative Q-Learning. CoRR Yutaka Shimizu, Joey Hong, Sergey Levine, Masayoshi Tomizuka
2024	A*	`conf`	The False Promise of Imitating Proprietary Language Models. ICLR Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song
2024	J	`jnl`	The Ingredients for Robotic Diffusion Transformers. CoRR Sudeep Dasari, Oier Mees, Sebastian Zhao, Mohan Kumar Srirama, Sergey Levine
2024	A*	`conf`	Training Diffusion Models with Reinforcement Learning. ICLR Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine
2024	J	`jnl`	Traversability-Aware Legged Navigation by Learning from Real-World Visual Data. CoRR Hongbo Zhang, Zhongyu Li, Xuanqi Zeng, Laura Smith, Kyle Stachowicz, Dhruv Shah, Linzhu Yue, Zhitao Song, Weipeng Xia, Sergey Levine, Koushil Sreenath, Yun-Hui Liu
2024	J	`jnl`	Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review. CoRR Masatoshi Uehara, Yulai Zhao, Tommaso Biancalani, Sergey Levine
2024	J	`jnl`	Unfamiliar Finetuning Examples Control How Language Models Hallucinate. CoRR Katie Kang, Eric Wallace, Claire J. Tomlin, Aviral Kumar, Sergey Levine
2024	A*	`conf`	Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings. ICML Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine
2024	J	`jnl`	Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings. CoRR Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine
2024	J	`jnl`	Unsupervised-to-Online Reinforcement Learning. CoRR Junsu Kim, Seohong Park, Sergey Levine
2024	J	`jnl`	Video Occupancy Models. CoRR Manan Tomar, Philippe Hansen-Estruch, Philip Bachman, Alex Lamb, John Langford, Matthew E. Taylor, Sergey Levine
2024	J	`jnl`	Vision-Language Models Provide Promptable Representations for Reinforcement Learning. CoRR William Chen, Oier Mees, Aviral Kumar, Sergey Levine
2024	J	`jnl`	What Do Learning Dynamics Reveal About Generalization in LLM Reasoning? CoRR Katie Kang, Amrith Setlur, Dibya Ghosh, Jacob Steinhardt, Claire J. Tomlin, Sergey Levine, Aviral Kumar
2024	—	`conf`	Yell At Your Robot: Improving On-the-Fly from Language Corrections. Robotics: Science and Systems Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn
2024	J	`jnl`	Yell At Your Robot: Improving On-the-Fly from Language Corrections. CoRR Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn
2024	A*	`conf`	Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models. ICLR Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Rich Walke, Chelsea Finn, Aviral Kumar, Sergey Levine
2024	J	`jnl`	π CoRR Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, Liyiming Ke, Sergey Levine, Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Lucy Xiaoyang Shi, James Tanner, Quan Vuong, Anna Walling, Haohuan Wang, Ury Zhilinsky
2023	A*	`conf`	A Connection between One-Step RL and Critic Regularization in Reinforcement Learning. ICML Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov
2023	J	`jnl`	A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning. CoRR Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov
2023	A*	`conf`	Accelerating Exploration with Unlabeled Prior Data. NeurIPS Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
2023	J	`jnl`	Accelerating Exploration with Unlabeled Prior Data. CoRR Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
2023	Misc	`conf`	Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning. CoRL Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine
2023	J	`jnl`	Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning. CoRR Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine
2023	J	`jnl`	Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment. CoRR Annie S. Chen, Govind Chada, Laura Smith, Archit Sharma, Zipeng Fu, Sergey Levine, Chelsea Finn
2023	A*	`ed.`	Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023. NeurIPS Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine
2023	A*	`conf`	Adversarial Policies Beat Superhuman Go AIs. ICML 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	A*	`conf`	Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. ICLR Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine
2023	J	`jnl`	Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. CoRR Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine
2023	A	`conf`	Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning. IROS Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine
2023	J	`jnl`	Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning. CoRR Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine
2023	Misc	`conf`	BridgeData V2: A Dataset for Robot Learning at Scale. CoRL 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	J	`jnl`	BridgeData V2: A Dataset for Robot Learning at Scale. CoRR 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
2023	A*	`conf`	Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning. NeurIPS Mitsuhiko Nakamoto, Simon Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine
2023	J	`jnl`	Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning. CoRR Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine
2023	J	`jnl`	Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. CoRR Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter
2023	J	`jnl`	Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts. CoRR Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn
2023	A*	`conf`	Confidence-Conditioned Value Functions for Offline Reinforcement Learning. ICLR Joey Hong, Aviral Kumar, Sergey Levine
2023	—	`conf`	Contrastive Example-Based Control. L4DC Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
2023	J	`jnl`	Contrastive Example-Based Control. CoRR Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
2023	J	`jnl`	Deep Neural Networks Tend To Extrapolate Predictably. CoRR Katie Kang, Amrith Setlur, Claire J. Tomlin, Sergey Levine
2023	—	`conf`	Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. Robotics: Science and Systems 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 T. 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
2023	J	`jnl`	Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. CoRR 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, Jeffrey T. 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
2023	—	`conf`	Demonstrating A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning. Robotics: Science and Systems Ilya Kostrikov, Laura Smith, Sergey Levine
2023	A*	`conf`	Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. ICRA Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman
2023	A*	`conf`	Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance. ICRA Kelvin Xu, Zheyuan Hu, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine
2023	A*	`conf`	Efficient Deep Reinforcement Learning Requires Regulating Overfitting. ICLR Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine
2023	J	`jnl`	Efficient Deep Reinforcement Learning Requires Regulating Overfitting. CoRR Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine
2023	A*	`conf`	Efficient Online Reinforcement Learning with Offline Data. ICML Philip J. Ball, Laura Smith, Ilya Kostrikov, Sergey Levine
2023	J	`jnl`	Efficient Online Reinforcement Learning with Offline Data. CoRR Philip J. Ball, Laura Smith, Ilya Kostrikov, Sergey Levine
2023	A*	`conf`	ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation. ICRA Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine
2023	Misc	`conf`	FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing. CoRL Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine
2023	J	`jnl`	FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing. CoRR Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine
2023	A*	`conf`	GNM: A General Navigation Model to Drive Any Robot. ICRA Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, Sergey Levine
2023	Misc	`conf`	Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL 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	J	`jnl`	Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRR Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
2023	A*	`conf`	Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents. NeurIPS Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter
2023	J	`jnl`	Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control. CoRR Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter
2023	J	`jnl`	Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion. CoRR Laura Smith, Yunhao Cao, Sergey Levine
2023	A*	`conf`	HIQL: Offline Goal-Conditioned RL with Latent States as Actions. NeurIPS Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
2023	J	`jnl`	HIQL: Offline Goal-Conditioned RL with Latent States as Actions. CoRR Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
2023	A*	`conf`	Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. ICLR Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang
2023	J	`jnl`	IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies. CoRR Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine
2023	A*	`conf`	Ignorance is Bliss: Robust Control via Information Gating. NeurIPS Manan Tomar, Riashat Islam, Matthew E. Taylor, Sergey Levine, Philip Bachman
2023	J	`jnl`	Ignorance is Bliss: Robust Control via Information Gating. CoRR Manan Tomar, Riashat Islam, Sergey Levine, Philip Bachman
2023	A	`conf`	Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. IROS Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine
2023	J	`jnl`	Improving Generalization with Approximate Factored Value Functions. Trans. Mach. Learn. Res. Shagun Sodhani, Sergey Levine, Amy Zhang
2023	A*	`conf`	Jump-Start Reinforcement Learning. ICML Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman
2023	J	`jnl`	LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models. CoRR Marwa Abdulhai, Isadora White, Charlie Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine
2023	J	`jnl`	Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction. CoRR Han Qi, Xinyang Geng, Stefano Rando, Iku Ohama, Aviral Kumar, Sergey Levine
2023	—	`conf`	Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware. Robotics: Science and Systems Tony Z. Zhao, Vikash Kumar, Sergey Levine, Chelsea Finn
2023	J	`jnl`	Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware. CoRR Tony Z. Zhao, Vikash Kumar, Sergey Levine, Chelsea Finn
2023	—	`conf`	Learning and Adapting Agile Locomotion Skills by Transferring Experience. Robotics: Science and Systems Laura Smith, J. Chase Kew, Tianyu Li, Linda Luu, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine
2023	J	`jnl`	Learning and Adapting Agile Locomotion Skills by Transferring Experience. CoRR Laura Smith, J. Chase Kew, Tianyu Li, Linda Luu, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine
2023	A*	`conf`	Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for Industrial Insertion of Novel Connectors from Vision. ICRA Ashvin Nair, Brian Zhu, Gokul Narayanan, Eugen Solowjow, Sergey Levine
2023	A*	`conf`	Learning to Influence Human Behavior with Offline Reinforcement Learning. NeurIPS Joey Hong, Sergey Levine, Anca D. Dragan
2023	J	`jnl`	Learning to Influence Human Behavior with Offline Reinforcement Learning. CoRR Joey Hong, Anca D. Dragan, Sergey Levine
2023	J	`jnl`	METRA: Scalable Unsupervised RL with Metric-Aware Abstraction. CoRR Seohong Park, Oleh Rybkin, Sergey Levine
2023	J	`jnl`	Multi-Stage Cable Routing through Hierarchical Imitation Learning. CoRR Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, Sergey Levine
2023	—	`conf`	Multi-Task Imitation Learning for Linear Dynamical Systems. L4DC Thomas T. C. K. Zhang, Katie Kang, Bruce D. Lee, Claire J. Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni
2023	Misc	`conf`	Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning. CoRL Dhruv Shah, Michael Robert Equi, Blazej Osinski, Fei Xia, Brian Ichter, Sergey Levine
2023	J	`jnl`	Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning. CoRR Dhruv Shah, Michael Equi, Blazej Osinski, Fei Xia, Brian Ichter, Sergey Levine
2023	J	`jnl`	Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. CoRR Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang
2023	J	`jnl`	NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration. CoRR Ajay Sridhar, Dhruv Shah, Catherine Glossop, Sergey Levine
2023	A*	`conf`	Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes. ICLR Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine
2023	A*	`conf`	Offline RL for Natural Language Generation with Implicit Language Q Learning. ICLR Charlie Snell, Ilya Kostrikov, Yi Su, Sherry Yang, Sergey Levine
2023	J	`jnl`	Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. CoRR Joey Hong, Anca D. Dragan, Sergey Levine
2023	J	`jnl`	Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias. CoRR Max Sobol Mark, Archit Sharma, Fahim Tajwar, Rafael Rafailov, Sergey Levine, Chelsea Finn
2023	A*	`conf`	PaLM-E: An Embodied Multimodal Language Model. ICML 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	J	`jnl`	PaLM-E: An Embodied Multimodal Language Model. CoRR 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	—	`conf`	Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials. Robotics: Science and Systems Aviral Kumar, Anikait Singh, Frederik D. Ebert, Mitsuhiko Nakamoto, Yanlai Yang, Chelsea Finn, Sergey Levine
2023	A*	`conf`	Predictable MDP Abstraction for Unsupervised Model-Based RL. ICML Seohong Park, Sergey Levine
2023	J	`jnl`	Predictable MDP Abstraction for Unsupervised Model-Based RL. CoRR Seohong Park, Sergey Levine
2023	J	`jnl`	Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features. CoRR Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn
2023	Misc	`conf`	Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRL 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	J	`jnl`	Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRR 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
2023	Misc	`conf`	REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. CoRL Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine
2023	J	`jnl`	REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. CoRR Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine
2023	J	`jnl`	RLIF: Interactive Imitation Learning as Reinforcement Learning. CoRR Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine
2023	—	`conf`	RT-1: Robotics Transformer for Real-World Control at Scale. Robotics: Science and Systems 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
2023	Misc	`conf`	RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRL 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	J	`jnl`	RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRR 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
2023	A*	`conf`	ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints. NeurIPS Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine
2023	A*	`conf`	Reinforcement Learning from Passive Data via Latent Intentions. ICML Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine
2023	J	`jnl`	Reinforcement Learning from Passive Data via Latent Intentions. CoRR Dibya Ghosh, Chethan Bhateja, Sergey Levine
2023	J	`jnl`	Robotic Offline RL from Internet Videos via Value-Function Pre-Training. CoRR Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar
2023	—	`conf`	Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models. Robotics: Science and Systems Ted Xiao, Harris Chan, Pierre Sermanet, Ayzaan Wahid, Anthony Brohan, Karol Hausman, Sergey Levine, Jonathan Tompson
2023	J	`jnl`	Robust and Versatile Bipedal Jumping Control through Multi-Task Reinforcement Learning. CoRR Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath
2023	—	`conf`	Robust and Versatile Bipedal Jumping Control through Reinforcement Learning. Robotics: Science and Systems Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath
2023	J	`jnl`	SACSoN: Scalable Autonomous Data Collection for Social Navigation. CoRR Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine
2023	A*	`conf`	Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. ICLR Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov
2023	J	`jnl`	Stabilizing Contrastive RL: Techniques for Offline Goal Reaching. CoRR Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine
2023	J	`jnl`	The False Promise of Imitating Proprietary LLMs. CoRR Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song
2023	J	`jnl`	Training Diffusion Models with Reinforcement Learning. CoRR Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine
2023	A*	`conf`	Understanding the Complexity Gains of Single-Task RL with a Curriculum. ICML Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine
2023	Misc	`conf`	ViNT: A Foundation Model for Visual Navigation. CoRL Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine
2023	J	`jnl`	ViNT: A Foundation Model for Visual Navigation. CoRR Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine
2023	J	`jnl`	Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations. CoRR Joey Hong, Sergey Levine, Anca D. Dragan
2023	J	`jnl`	Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models. CoRR Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Walke, Chelsea Finn, Aviral Kumar, Sergey Levine
2022	J	`jnl`	A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning. CoRR Laura Smith, Ilya Kostrikov, Sergey Levine
2022	J	`jnl`	ASE: Large-Scale Reusable Adversarial Skill Embeddings for Physically Simulated Characters. CoRR Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, Sanja Fidler
2022	J	`jnl`	ASE: large-scale reusable adversarial skill embeddings for physically simulated characters. ACM Trans. Graph. Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, Sanja Fidler
2022	A*	`conf`	ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning. ICRA Sean Chen, Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine
2022	J	`jnl`	ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning. CoRR Sean Chen, Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine
2022	J	`jnl`	Adversarial Policies Beat Professional-Level Go AIs. CoRR Tony Tong Wang, Adam Gleave, Nora Belrose, Tom Tseng, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell
2022	A*	`conf`	Adversarial Unlearning: Reducing Confidence Along Adversarial Directions. NeurIPS Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine
2022	J	`jnl`	Adversarial Unlearning: Reducing Confidence Along Adversarial Directions. CoRR Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine
2022	A*	`conf`	Autonomous Reinforcement Learning: Formalism and Benchmarking. ICLR Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn
2022	J	`jnl`	BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning. CoRR Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, Chelsea Finn
2022	J	`jnl`	Basis for Intentions: Efficient Inverse Reinforcement Learning using Past Experience. CoRR Marwa Abdulhai, Natasha Jaques, Sergey Levine
2022	A*	`conf`	Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning. ICML Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine
2022	J	`jnl`	Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning. CoRR Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine
2022	—	`conf`	Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets. Robotics: Science and Systems Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine
2022	A*	`conf`	C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. ICLR Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez
2022	—	`conf`	CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning. NAACL-HLT Siddharth Verma, Justin Fu, Sherry Yang, Sergey Levine
2022	J	`jnl`	CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning. CoRR Siddharth Verma, Justin Fu, Mengjiao Yang, Sergey Levine
2022	A*	`conf`	CoMPS: Continual Meta Policy Search. ICLR Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine
2022	J	`jnl`	Confidence-Conditioned Value Functions for Offline Reinforcement Learning. CoRR Joey Hong, Aviral Kumar, Sergey Levine
2022	—	`conf`	Context-Aware Language Modeling for Goal-Oriented Dialogue Systems. NAACL-HLT (Findings) Charlie Snell, Sherry Yang, Justin Fu, Yi Su, Sergey Levine
2022	J	`jnl`	Context-Aware Language Modeling for Goal-Oriented Dialogue Systems. CoRR Charlie Snell, Mengjiao Yang, Justin Fu, Yi Su, Sergey Levine
2022	A*	`conf`	Contrastive Learning as Goal-Conditioned Reinforcement Learning. NeurIPS Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov
2022	J	`jnl`	Contrastive Learning as Goal-Conditioned Reinforcement Learning. CoRR Benjamin Eysenbach, Tianjun Zhang, Ruslan Salakhutdinov, Sergey Levine
2022	A*	`conf`	Control-Aware Prediction Objectives for Autonomous Driving. ICRA Rowan McAllister, Blake Wulfe, Jean Mercat, Logan Ellis, Sergey Levine, Adrien Gaidon
2022	J	`jnl`	Control-Aware Prediction Objectives for Autonomous Driving. CoRR Rowan McAllister, Blake Wulfe, Jean Mercat, Logan Ellis, Sergey Levine, Adrien Gaidon
2022	A*	`conf`	DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning. NeurIPS Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar
2022	A*	`conf`	DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. ICLR Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine
2022	A*	`conf`	Data-Driven Offline Decision-Making via Invariant Representation Learning. NeurIPS Han Qi, Yi Su, Aviral Kumar, Sergey Levine
2022	J	`jnl`	Data-Driven Offline Decision-Making via Invariant Representation Learning. CoRR Han Qi, Yi Su, Aviral Kumar, Sergey Levine
2022	A*	`conf`	Data-Driven Offline Optimization for Architecting Hardware Accelerators. ICLR Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine
2022	J	`jnl`	Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. CoRR Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman
2022	A*	`conf`	Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization. ICML Brandon Trabucco, Xinyang Geng, Aviral Kumar, Sergey Levine
2022	J	`jnl`	Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization. CoRR Brandon Trabucco, Xinyang Geng, Aviral Kumar, Sergey Levine
2022	J	`jnl`	Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance. CoRR Kelvin Xu, Zheyuan Hu, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine
2022	A*	`conf`	Distributionally Adaptive Meta Reinforcement Learning. NeurIPS Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
2022	J	`jnl`	Distributionally Adaptive Meta Reinforcement Learning. CoRR Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
2022	Misc	`conf`	Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. CoRL 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	J	`jnl`	Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. CoRR Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan
2022	Misc	`conf`	Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning. CoRL Homer Walke, Jonathan Yang, Albert Yu, Aviral Kumar, Jedrzej Orbik, Avi Singh, Sergey Levine
2022	J	`jnl`	Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning. CoRR Homer Walke, Jonathan Yang, Albert Yu, Aviral Kumar, Jedrzej Orbik, Avi Singh, Sergey Levine
2022	J	`jnl`	Dual Generator Offline Reinforcement Learning. CoRR Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar
2022	J	`jnl`	ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation. CoRR Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine
2022	A*	`conf`	Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 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	J	`jnl`	FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners. CoRR Hao Liu, Xinyang Geng, Lisa Lee, Igor Mordatch, Sergey Levine, Sharan Narang, Pieter Abbeel
2022	A*	`conf`	First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization. NeurIPS Siddharth Reddy, Sergey Levine, Anca D. Dragan
2022	J	`jnl`	First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization. CoRR Siddharth Reddy, Sergey Levine, Anca D. Dragan
2022	J	`jnl`	Fully Online Meta-Learning Without Task Boundaries. CoRR Jathushan Rajasegaran, Chelsea Finn, Sergey Levine
2022	J	`jnl`	GNM: A General Navigation Model to Drive Any Robot. CoRR Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, Sergey Levine
2022	Misc	`conf`	GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots. CoRL Gilbert Feng, Hongbo Zhang, Zhongyu Li, Xue Bin Peng, Bhuvan Basireddy, Linzhu Yue, Zhitao Song, Lizhi Yang, Yunhui Liu, Koushil Sreenath, Sergey Levine
2022	J	`jnl`	GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots. CoRR Gilbert Feng, Hongbo Zhang, Zhongyu Li, Xue Bin Peng, Bhuvan Basireddy, Linzhu Yue, Zhitao Song, Lizhi Yang, Yunhui Liu, Koushil Sreenath, Sergey Levine
2022	Misc	`conf`	Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks. CoRL Kuan Fang, Patrick Yin, Ashvin Nair, Homer Walke, Gengchen Yan, Sergey Levine
2022	J	`jnl`	Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks. CoRR Kuan Fang, Patrick Yin, Ashvin Nair, Homer Walke, Gengchen Yan, Sergey Levine
2022	A	`conf`	Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot. IROS Yandong Ji, Zhongyu Li, Yinan Sun, Xue Bin Peng, Sergey Levine, Glen Berseth, Koushil Sreenath
2022	J	`jnl`	Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot. CoRR Yandong Ji, Zhongyu Li, Yinan Sun, Xue Bin Peng, Sergey Levine, Glen Berseth, Koushil Sreenath
2022	A*	`conf`	How to Leverage Unlabeled Data in Offline Reinforcement Learning. ICML Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine
2022	J	`jnl`	How to Leverage Unlabeled Data in Offline Reinforcement Learning. CoRR Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine
2022	A*	`conf`	Hybrid Imitative Planning with Geometric and Predictive Costs in Off-road Environments. ICRA Nitish Dashora, Daniel Shin, Dhruv Shah, Henry A. Leopold, David D. Fan, Ali-Akbar Agha-Mohammadi, Nicholas Rhinehart, Sergey Levine
2022	J	`jnl`	INFOrmation Prioritization through EmPOWERment in Visual Model-Based RL. CoRR Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine
2022	A*	`conf`	Imitating Past Successes can be Very Suboptimal. NeurIPS Benjamin Eysenbach, Soumith Udatha, Russ Salakhutdinov, Sergey Levine
2022	J	`jnl`	Imitating Past Successes can be Very Suboptimal. CoRR Benjamin Eysenbach, Soumith Udatha, Sergey Levine, Ruslan Salakhutdinov
2022	J	`jnl`	Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. CoRR Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine
2022	A*	`conf`	Information Prioritization through Empowerment in Visual Model-based RL. ICLR Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine
2022	Misc	`conf`	Inner Monologue: Embodied Reasoning through Planning with Language Models. CoRL 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	J	`jnl`	Inner Monologue: Embodied Reasoning through Planning with Language Models. CoRR Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, Pierre Sermanet, Noah Brown, Tomas Jackson, Linda Luu, Sergey Levine, Karol Hausman, Brian Ichter
2022	Misc	`conf`	Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty. CoRL Charles Packer, Nicholas Rhinehart, Rowan Thomas McAllister, Matthew A. Wright, Xin Wang, Jeff He, Sergey Levine, Joseph E. Gonzalez
2022	J	`jnl`	Jump-Start Reinforcement Learning. CoRR Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman
2022	Misc	`conf`	LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action. CoRL Dhruv Shah, Blazej Osinski, Brian Ichter, Sergey Levine
2022	J	`jnl`	LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action. CoRR Dhruv Shah, Blazej Osinski, Brian Ichter, Sergey Levine
2022	J	`jnl`	Learning Robotic Navigation from Experience: Principles, Methods, and Recent Results. CoRR Sergey Levine, Dhruv Shah
2022	J	`jnl`	Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for Industrial Insertion of Novel Connectors from Vision. CoRR Ashvin Nair, Brian Zhu, Gokul Narayanan, Eugen Solowjow, Sergey Levine
2022	A*	`conf`	Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World. ICRA Laura Smith, J. Chase Kew, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine
2022	A*	`conf`	Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control. ICML Katie Kang, Paula Gradu, Jason J. Choi, Michael Janner, Claire J. Tomlin, Sergey Levine
2022	J	`jnl`	Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control. CoRR Katie Kang, Paula Gradu, Jason J. Choi, Michael Janner, Claire J. Tomlin, Sergey Levine
2022	A*	`conf`	MEMO: Test Time Robustness via Adaptation and Augmentation. NeurIPS Marvin Zhang, Sergey Levine, Chelsea Finn
2022	A*	`conf`	Maximum Entropy RL (Provably) Solves Some Robust RL Problems. ICLR Benjamin Eysenbach, Sergey Levine
2022	A*	`conf`	Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. NeurIPS Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov
2022	J	`jnl`	Multi-Task Imitation Learning for Linear Dynamical Systems. CoRR Thomas T. C. K. Zhang, Katie Kang, Bruce D. Lee, Claire J. Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni
2022	J	`jnl`	Multimodal Masked Autoencoders Learn Transferable Representations. CoRR Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurams, Sergey Levine, Pieter Abbeel
2022	A*	`conf`	Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation. NeurIPS Michael Chang, Tom Griffiths, Sergey Levine
2022	J	`jnl`	Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation. CoRR Michael Chang, Thomas L. Griffiths, Sergey Levine
2022	A*	`conf`	Offline Meta-Reinforcement Learning for Industrial Insertion. ICRA Tony Z. Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jon Scholz, Stefan Schaal, Sergey Levine
2022	A*	`conf`	Offline Meta-Reinforcement Learning with Online Self-Supervision. ICML Vitchyr H. Pong, Ashvin Nair, Laura Smith, Catherine Huang, Sergey Levine
2022	J	`jnl`	Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes. CoRR Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine
2022	A*	`conf`	Offline RL Policies Should Be Trained to be Adaptive. ICML Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
2022	J	`jnl`	Offline RL Policies Should be Trained to be Adaptive. CoRR Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
2022	J	`jnl`	Offline RL With Realistic Datasets: Heteroskedasticity and Support Constraints. CoRR Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine
2022	J	`jnl`	Offline RL for Natural Language Generation with Implicit Language Q Learning. CoRR Charlie Snell, Ilya Kostrikov, Yi Su, Mengjiao Yang, Sergey Levine
2022	Misc	`conf`	Offline Reinforcement Learning for Visual Navigation. CoRL Dhruv Shah, Arjun Bhorkar, Hrishit Leen, Ilya Kostrikov, Nicholas Rhinehart, Sergey Levine
2022	J	`jnl`	Offline Reinforcement Learning for Visual Navigation. CoRR Dhruv Shah, Arjun Bhorkar, Hrish Leen, Ilya Kostrikov, Nick Rhinehart, Sergey Levine
2022	A*	`conf`	Offline Reinforcement Learning with Implicit Q-Learning. ICLR Ilya Kostrikov, Ashvin Nair, Sergey Levine
2022	A	`conf`	Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space. IROS Kuan Fang, Patrick Yin, Ashvin Nair, Sergey Levine
2022	J	`jnl`	Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space. CoRR Kuan Fang, Patrick Yin, Ashvin Nair, Sergey Levine
2022	A*	`conf`	Planning with Diffusion for Flexible Behavior Synthesis. ICML Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine
2022	J	`jnl`	Planning with Diffusion for Flexible Behavior Synthesis. CoRR Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine
2022	J	`jnl`	Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials. CoRR Aviral Kumar, Anikait Singh, Frederik Ebert, Yanlai Yang, Chelsea Finn, Sergey Levine
2022	J	`jnl`	RT-1: Robotics Transformer for Real-World Control at Scale. CoRR 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 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
2022	J	`jnl`	Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models. CoRR Ted Xiao, Harris Chan, Pierre Sermanet, Ayzaan Wahid, Anthony Brohan, Karol Hausman, Sergey Levine, Jonathan Tompson
2022	A*	`conf`	RvS: What is Essential for Offline RL via Supervised Learning? ICLR Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine
2022	A*	`conf`	Should I Run Offline Reinforcement Learning or Behavioral Cloning? ICLR Aviral Kumar, Joey Hong, Anikait Singh, Sergey Levine
2022	J	`jnl`	Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. CoRR Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov
2022	A*	`conf`	TRAIL: Near-Optimal Imitation Learning with Suboptimal Data. ICLR Mengjiao Yang, Sergey Levine, Ofir Nachum
2022	A*	`conf`	The Information Geometry of Unsupervised Reinforcement Learning. ICLR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2022	J	`jnl`	Understanding the Complexity Gains of Single-Task RL with a Curriculum. CoRR Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine
2022	A*	`conf`	Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. NeurIPS Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine
2022	J	`jnl`	Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. CoRR Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine
2022	A*	`conf`	Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning. ICLR Dhruv Shah, Peng Xu, Yao Lu, Ted Xiao, Alexander Toshev, Sergey Levine, Brian Ichter
2022	—	`conf`	ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints. Robotics: Science and Systems Dhruv Shah, Sergey Levine
2022	J	`jnl`	ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints. CoRR Dhruv Shah, Sergey Levine
2022	J	`jnl`	When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning? CoRR Aviral Kumar, Joey Hong, Anikait Singh, Sergey Levine
2022	J	`jnl`	X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback. CoRR Jensen Gao, Siddharth Reddy, Glen Berseth, Nicholas Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca D. Dragan, Sergey Levine
2022	A*	`conf`	You Only Live Once: Single-Life Reinforcement Learning. NeurIPS Annie S. Chen, Archit Sharma, Sergey Levine, Chelsea Finn
2022	J	`jnl`	You Only Live Once: Single-Life Reinforcement Learning. CoRR Annie S. Chen, Archit Sharma, Sergey Levine, Chelsea Finn
2021	Misc	`conf`	A Workflow for Offline Model-Free Robotic Reinforcement Learning. CoRL Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine
2021	J	`jnl`	A Workflow for Offline Model-Free Robotic Reinforcement Learning. CoRR Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine
2021	J	`jnl`	AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control. CoRR Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa
2021	J	`jnl`	AMP: adversarial motion priors for stylized physics-based character control. ACM Trans. Graph. Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa
2021	J	`jnl`	AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale. CoRR Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine
2021	Misc	`conf`	AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale. CoRL Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine
2021	A*	`conf`	Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. ICML Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine
2021	J	`jnl`	Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. CoRR Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jake Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine
2021	A*	`conf`	Adaptive Risk Minimization: Learning to Adapt to Domain Shift. NeurIPS Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn
2021	A*	`conf`	Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation. ICML Aurick Zhou, Sergey Levine
2021	A*	`conf`	Autonomous Reinforcement Learning via Subgoal Curricula. NeurIPS Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
2021	J	`jnl`	Autonomous Reinforcement Learning: Formalism and Benchmarking. CoRR Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn
2021	J	`jnl`	BADGR: An Autonomous Self-Supervised Learning-Based Navigation System. IEEE Robotics Autom. Lett. Gregory Kahn, Pieter Abbeel, Sergey Levine
2021	Misc	`conf`	BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning. CoRL Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, Chelsea Finn
2021	A*	`conf`	Bayesian Adaptation for Covariate Shift. NeurIPS Aurick Zhou, Sergey Levine
2021	A*	`conf`	Benchmarks for Deep Off-Policy Evaluation. ICLR 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	J	`jnl`	Benchmarks for Deep Off-Policy Evaluation. CoRR 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	J	`jnl`	Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets. CoRR Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine
2021	A*	`conf`	C-Learning: Learning to Achieve Goals via Recursive Classification. ICLR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	J	`jnl`	C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. CoRR Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez
2021	A*	`conf`	COMBO: Conservative Offline Model-Based Policy Optimization. NeurIPS Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn
2021	J	`jnl`	COMBO: Conservative Offline Model-Based Policy Optimization. CoRR Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn
2021	J	`jnl`	CoMPS: Continual Meta Policy Search. CoRR Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine
2021	A*	`conf`	Conservative Data Sharing for Multi-Task Offline Reinforcement Learning. NeurIPS Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
2021	J	`jnl`	Conservative Data Sharing for Multi-Task Offline Reinforcement Learning. CoRR Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
2021	A*	`conf`	Conservative Objective Models for Effective Offline Model-Based Optimization. ICML Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine
2021	J	`jnl`	Conservative Objective Models for Effective Offline Model-Based Optimization. CoRR Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine
2021	A*	`conf`	Conservative Safety Critics for Exploration. ICLR Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg
2021	A*	`conf`	Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models. ICRA Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine
2021	J	`jnl`	Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models. CoRR Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine
2021	J	`jnl`	DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. CoRR Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine
2021	J	`jnl`	Data-Driven Offline Optimization For Architecting Hardware Accelerators. CoRR Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine
2021	A*	`conf`	DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies. ICRA Soroush Nasiriany, Vitchyr H. Pong, Ashvin Nair, Alexander Khazatsky, Glen Berseth, Sergey Levine
2021	J	`jnl`	DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies. CoRR Soroush Nasiriany, Vitchyr H. Pong, Ashvin Nair, Alexander Khazatsky, Glen Berseth, Sergey Levine
2021	A*	`conf`	Emergent Social Learning via Multi-agent Reinforcement Learning. ICML Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques
2021	A*	`conf`	Evolving Reinforcement Learning Algorithms. ICLR John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust
2021	J	`jnl`	Evolving Reinforcement Learning Algorithms. CoRR John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust
2021	J	`jnl`	Explore and Control with Adversarial Surprise. CoRR Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, Sergey Levine
2021	J	`jnl`	Extending the WILDS Benchmark for Unsupervised Adaptation. CoRR 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
2021	A*	`conf`	Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. ICLR Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer
2021	J	`jnl`	FitVid: Overfitting in Pixel-Level Video Prediction. CoRR Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan
2021	Misc	`conf`	Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation. CoRL Charles Sun, Jedrzej Orbik, Coline Manon Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine
2021	Misc	`conf`	Hierarchically Integrated Models: Learning to Navigate from Heterogeneous Robots. CoRL Katie Kang, Gregory Kahn, Sergey Levine
2021	J	`jnl`	How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned. CoRR Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine
2021	J	`jnl`	How to train your robot with deep reinforcement learning: lessons we have learned. Int. J. Robotics Res. Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine
2021	J	`jnl`	Hybrid Imitative Planning with Geometric and Predictive Costs in Off-road Environments. CoRR Nitish Dashora, Daniel Shin, Dhruv Shah, Henry A. Leopold, David D. Fan, Ali-Akbar Agha-Mohammadi, Nicholas Rhinehart, Sergey Levine
2021	A*	`conf`	Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. ICLR Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
2021	A*	`conf`	Information is Power: Intrinsic Control via Information Capture. NeurIPS Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine
2021	J	`jnl`	Information is Power: Intrinsic Control via Information Capture. CoRR Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine
2021	J	`jnl`	LaND: Learning to Navigate From Disengagements. IEEE Robotics Autom. Lett. Gregory Kahn, Pieter Abbeel, Sergey Levine
2021	A*	`conf`	Learning Invariant Representations for Reinforcement Learning without Reconstruction. ICLR Amy Zhang, Rowan Thomas McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
2021	A*	`conf`	Learning to Reach Goals via Iterated Supervised Learning. ICLR Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine
2021	J	`jnl`	Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World. CoRR Laura Smith, J. Chase Kew, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine
2021	J	`jnl`	MEMO: Test Time Robustness via Adaptation and Augmentation. CoRR Marvin Zhang, Sergey Levine, Chelsea Finn
2021	J	`jnl`	MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale. CoRR Dmitry Kalashnikov, Jacob Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, Karol Hausman
2021	A*	`conf`	MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning. ICML Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr H. Pong, Aurick Zhou, Justin Yu, Sergey Levine
2021	J	`jnl`	MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning. CoRR Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine
2021	J	`jnl`	Maximum Entropy RL (Provably) Solves Some Robust RL Problems. CoRR Benjamin Eysenbach, Sergey Levine
2021	J	`jnl`	Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. CoRR Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov
2021	J	`jnl`	Model-Based Meta-Reinforcement Learning for Flight With Suspended Payloads. IEEE Robotics Autom. Lett. Suneel Belkhale, Rachel Li, Gregory Kahn, Rowan McAllister, Roberto Calandra, Sergey Levine
2021	A*	`conf`	Model-Based Reinforcement Learning via Latent-Space Collocation. ICML Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine
2021	J	`jnl`	Model-Based Reinforcement Learning via Latent-Space Collocation. CoRR Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine
2021	A*	`conf`	Model-Based Visual Planning with Self-Supervised Functional Distances. ICLR Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine
2021	A*	`conf`	Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment. ICML Michael Chang, Sidhant Kaushik, Sergey Levine, Tom Griffiths
2021	J	`jnl`	Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment. CoRR Michael Chang, Sidhant Kaushik, Sergey Levine, Thomas L. Griffiths
2021	J	`jnl`	Multi-Robot Deep Reinforcement Learning for Mobile Navigation. CoRR Katie Kang, Gregory Kahn, Sergey Levine
2021	A*	`conf`	OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. ICLR Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
2021	A*	`conf`	Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. ICLR Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov
2021	J	`jnl`	Offline Meta-Reinforcement Learning for Industrial Insertion. CoRR Tony Z. Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jonathan Scholz, Stefan Schaal, Sergey Levine
2021	A*	`conf`	Offline Meta-Reinforcement Learning with Advantage Weighting. ICML Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
2021	J	`jnl`	Offline Meta-Reinforcement Learning with Online Self-Supervision. CoRR Vitchyr H. Pong, Ashvin Nair, Laura Smith, Catherine Huang, Sergey Levine
2021	A*	`conf`	Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation. ICLR Justin Fu, Sergey Levine
2021	J	`jnl`	Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation. CoRR Justin Fu, Sergey Levine
2021	A*	`conf`	Offline Reinforcement Learning as One Big Sequence Modeling Problem. NeurIPS Michael Janner, Qiyang Li, Sergey Levine
2021	J	`jnl`	Offline Reinforcement Learning with Implicit Q-Learning. CoRR Ilya Kostrikov, Ashvin Nair, Sergey Levine
2021	A*	`conf`	Outcome-Driven Reinforcement Learning via Variational Inference. NeurIPS Tim G. J. Rudner, Vitchyr Pong, Rowan McAllister, Yarin Gal, Sergey Levine
2021	J	`jnl`	Outcome-Driven Reinforcement Learning via Variational Inference. CoRR Tim G. J. Rudner, Vitchyr H. Pong, Rowan McAllister, Yarin Gal, Sergey Levine
2021	A*	`conf`	Parrot: Data-Driven Behavioral Priors for Reinforcement Learning. ICLR Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
2021	J	`jnl`	Persistent Reinforcement Learning via Subgoal Curricula. CoRR Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
2021	A*	`conf`	Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning. ICML Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu
2021	J	`jnl`	Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning. CoRR Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu
2021	A*	`conf`	Pragmatic Image Compression for Human-in-the-Loop Decision-Making. NeurIPS Siddharth Reddy, Anca D. Dragan, Sergey Levine
2021	J	`jnl`	Pragmatic Image Compression for Human-in-the-Loop Decision-Making. CoRR Siddharth Reddy, Anca D. Dragan, Sergey Levine
2021	A*	`conf`	PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. ICML Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar
2021	J	`jnl`	PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. CoRR Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar
2021	J	`jnl`	RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models. CoRR Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine
2021	Misc	`conf`	Rapid Exploration for Open-World Navigation with Latent Goal Models. CoRL Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine
2021	J	`jnl`	ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors. CoRR Charles Sun, Jedrzej Orbik, Coline Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine
2021	A*	`conf`	Recurrent Independent Mechanisms. ICLR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2021	J	`jnl`	Reinforcement Learning as One Big Sequence Modeling Problem. CoRR Michael Janner, Qiyang Li, Sergey Levine
2021	A*	`conf`	Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots. ICRA Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath
2021	J	`jnl`	Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots. CoRR Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath
2021	A*	`conf`	Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. NeurIPS Ben Eysenbach, Sergey Levine, Ruslan Salakhutdinov
2021	J	`jnl`	Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. CoRR Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov
2021	A*	`conf`	Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention. ICRA Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine
2021	J	`jnl`	Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention. CoRR Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine
2021	A*	`conf`	Robust Predictable Control. NeurIPS Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	J	`jnl`	Robust Predictable Control. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	J	`jnl`	RvS: What is Essential for Offline RL via Supervised Learning? CoRR Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine
2021	A*	`conf`	SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments. ICLR Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
2021	Misc	`conf`	Scaling Up Multi-Task Robotic Reinforcement Learning. CoRL Dmitry Kalashnikov, Jake Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, Karol Hausman
2021	A*	`conf`	SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning. ICRA Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan
2021	J	`jnl`	SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning. CoRR Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan
2021	A*	`conf`	Simple and Effective VAE Training with Calibrated Decoders. ICML Oleh Rybkin, Kostas Daniilidis, Sergey Levine
2021	J	`jnl`	TRAIL: Near-Optimal Imitation Learning with Suboptimal Data. CoRR Mengjiao Yang, Sergey Levine, Ofir Nachum
2021	J	`jnl`	The Information Geometry of Unsupervised Reinforcement Learning. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	J	`jnl`	Training on Test Data with Bayesian Adaptation for Covariate Shift. CoRR Aurick Zhou, Sergey Levine
2021	Misc	`conf`	Understanding the World Through Action. CoRL Sergey Levine
2021	J	`jnl`	Understanding the World Through Action. CoRR Sergey Levine
2021	J	`jnl`	Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning. CoRR Dhruv Shah, Peng Xu, Yao Lu, Ted Xiao, Alexander Toshev, Sergey Levine, Brian Ichter
2021	J	`jnl`	Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning. CoRR Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu
2021	A*	`conf`	Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning. ICML Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu
2021	A*	`conf`	ViNG: Learning Open-World Navigation with Visual Goals. ICRA Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine
2021	A*	`conf`	WILDS: A Benchmark of in-the-Wild Distribution Shifts. ICML 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	A*	`conf`	What Can I Do Here? Learning New Skills by Imagining Visual Affordances. ICRA Alexander Khazatsky, Ashvin Nair, Daniel Jing, Sergey Levine
2021	J	`jnl`	What Can I Do Here? Learning New Skills by Imagining Visual Affordances. CoRR Alexander Khazatsky, Ashvin Nair, Daniel Jing, Sergey Levine
2021	A*	`conf`	Which Mutual-Information Representation Learning Objectives are Sufficient for Control? NeurIPS Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine
2021	J	`jnl`	Which Mutual-Information Representation Learning Objectives are Sufficient for Control? CoRR Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine
2021	A*	`conf`	Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. NeurIPS Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine
2021	J	`jnl`	Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. CoRR Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine
2021	A*	`conf`	X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback. ICLR Jensen Gao, Siddharth Reddy, Glen Berseth, Nicholas Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca D. Dragan, Sergey Levine
2020	—	`conf`	AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos. Robotics: Science and Systems Laura Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine
2020	J	`jnl`	Accelerating Online Reinforcement Learning with Offline Datasets. CoRR Ashvin Nair, Murtaza Dalal, Abhishek Gupta, Sergey Levine
2020	J	`jnl`	Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift. CoRR Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn
2020	A*	`conf`	Adversarial Policies: Attacking Deep Reinforcement Learning. ICLR Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell
2020	J	`jnl`	Amortized Conditional Normalized Maximum Likelihood. CoRR Aurick Zhou, Sergey Levine
2020	Misc	`conf`	Assisted Perception: Optimizing Observations to Communicate State. CoRL Siddharth Reddy, Sergey Levine, Anca D. Dragan
2020	J	`jnl`	Assisted Perception: Optimizing Observations to Communicate State. CoRR Siddharth Reddy, Sergey Levine, Anca D. Dragan
2020	J	`jnl`	BADGR: An Autonomous Self-Supervised Learning-Based Navigation System. CoRR Gregory Kahn, Pieter Abbeel, Sergey Levine
2020	J	`jnl`	C-Learning: Learning to Achieve Goals via Recursive Classification. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2020	J	`jnl`	COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning. CoRR Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine
2020	A*	`conf`	Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? ICML Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal
2020	J	`jnl`	Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? CoRR Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal
2020	A*	`conf`	Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. ICML Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman
2020	J	`jnl`	Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. CoRR Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman
2020	Misc	`conf`	Chaining Behaviors from Data with Model-Free Reinforcement Learning. CoRL Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine
2020	J	`jnl`	Cognitive Mapping and Planning for Visual Navigation. Int. J. Comput. Vis. Saurabh Gupta, Varun Tolani, James Davidson, Sergey Levine, Rahul Sukthankar, Jitendra Malik
2020	A*	`conf`	Conservative Q-Learning for Offline Reinforcement Learning. NeurIPS Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine
2020	J	`jnl`	Conservative Q-Learning for Offline Reinforcement Learning. CoRR Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine
2020	J	`jnl`	Conservative Safety Critics for Exploration. CoRR Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg
2020	A*	`conf`	Continual Learning of Control Primitives : Skill Discovery via Reset-Games. NeurIPS Kelvin Xu, Siddharth Verma, Chelsea Finn, Sergey Levine
2020	J	`jnl`	Continual Learning of Control Primitives: Skill Discovery via Reset-Games. CoRR Kelvin Xu, Siddharth Verma, Chelsea Finn, Sergey Levine
2020	J	`jnl`	D4RL: Datasets for Deep Data-Driven Reinforcement Learning. CoRR Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine
2020	A*	`conf`	Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions. ICML Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Tom Griffiths, Sergey Levine
2020	J	`jnl`	Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions. CoRR Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Thomas L. Griffiths, Sergey Levine
2020	A*	`conf`	Deep Imitative Models for Flexible Inference, Planning, and Control. ICLR Nicholas Rhinehart, Rowan McAllister, Sergey Levine
2020	A	`conf`	Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards. IROS Gerrit Schoettler, Ashvin Nair, Jianlan Luo, Shikhar Bahl, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine
2020	A*	`conf`	DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction. NeurIPS Aviral Kumar, Abhishek Gupta, Sergey Levine
2020	J	`jnl`	DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction. CoRR Aviral Kumar, Abhishek Gupta, Sergey Levine
2020	A*	`conf`	Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery. ICLR Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja, Sergey Levine
2020	A*	`conf`	Dynamics-Aware Unsupervised Discovery of Skills. ICLR Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman
2020	J	`jnl`	Ecological Reinforcement Learning. CoRR John D. Co-Reyes, Suvansh Sanjeev, Glen Berseth, Abhishek Gupta, Sergey Levine
2020	J	`jnl`	Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation. CoRR Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman
2020	A*	`conf`	Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. NeurIPS Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre M. Bayen, Stuart Russell, Andrew Critch, Sergey Levine
2020	J	`jnl`	Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. CoRR Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre M. Bayen, Stuart Russell, Andrew Critch, Sergey Levine
2020	—	`conf`	Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning. Robotics: Science and Systems Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu
2020	J	`jnl`	Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning. CoRR Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu
2020	A*	`conf`	Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. NeurIPS Michael Janner, Igor Mordatch, Sergey Levine
2020	A*	`conf`	Gradient Surgery for Multi-Task Learning. NeurIPS Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
2020	J	`jnl`	Gradient Surgery for Multi-Task Learning. CoRR Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
2020	J	`jnl`	Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. CoRR Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
2020	Misc	`conf`	Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting. CoRL Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart
2020	J	`jnl`	LaND: Learning to Navigate from Disengagements. CoRR Gregory Kahn, Pieter Abbeel, Sergey Levine
2020	—	`conf`	Learning Agile Robotic Locomotion Skills by Imitating Animals. Robotics: Science and Systems Xue Bin Peng, Erwin Coumans, Tingnan Zhang, Tsang-Wei Edward Lee, Jie Tan, Sergey Levine
2020	J	`jnl`	Learning Agile Robotic Locomotion Skills by Imitating Animals. CoRR Xue Bin Peng, Erwin Coumans, Tingnan Zhang, Tsang-Wei Edward Lee, Jie Tan, Sergey Levine
2020	A*	`conf`	Learning Human Objectives by Evaluating Hypothetical Behavior. ICML Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shane Legg, Jan Leike
2020	J	`jnl`	Learning Invariant Representations for Reinforcement Learning without Reconstruction. CoRR Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
2020	—	`conf`	Learning Predictive Models from Observation and Interaction. ECCV (20) Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn
2020	Misc	`conf`	Learning to Walk in the Real World with Minimal Human Effort. CoRL Sehoon Ha, Peng Xu, Zhenyu Tan, Sergey Levine, Jie Tan
2020	J	`jnl`	Learning to Walk in the Real World with Minimal Human Effort. CoRR Sehoon Ha, Peng Xu, Zhenyu Tan, Sergey Levine, Jie Tan
2020	A*	`conf`	Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. NeurIPS Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine
2020	J	`jnl`	Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. CoRR Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
2020	Misc	`conf`	MELD: Meta-Reinforcement Learning from Images via Latent State Models. CoRL Zihao Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine
2020	J	`jnl`	MELD: Meta-Reinforcement Learning from Images via Latent State Models. CoRR Tony Z. Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine
2020	A*	`conf`	MOPO: Model-based Offline Policy Optimization. NeurIPS Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma
2020	J	`jnl`	MOPO: Model-based Offline Policy Optimization. CoRR Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma
2020	A*	`conf`	Meta-Learning without Memorization. ICLR Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn
2020	J	`jnl`	Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling. CoRR Russell Mendonca, Xinyang Geng, Chelsea Finn, Sergey Levine
2020	A	`conf`	Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks. IROS Gerrit Schoettler, Ashvin Nair, Juan Aparicio Ojea, Sergey Levine, Eugen Solowjow
2020	J	`jnl`	Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks. CoRR Gerrit Schoettler, Ashvin Nair, Juan Aparicio Ojea, Sergey Levine, Eugen Solowjow
2020	A*	`conf`	Model Based Reinforcement Learning for Atari. ICLR 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	A*	`conf`	Model Inversion Networks for Model-Based Optimization. NeurIPS Aviral Kumar, Sergey Levine
2020	J	`jnl`	Model-Based Meta-Reinforcement Learning for Flight with Suspended Payloads. CoRR Suneel Belkhale, Rachel Li, Gregory Kahn, Rowan McAllister, Roberto Calandra, Sergey Levine
2020	J	`jnl`	Model-Based Visual Planning with Self-Supervised Functional Distances. CoRR Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine
2020	J	`jnl`	Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning. CoRR Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan
2020	J	`jnl`	Morphology-Agnostic Visual Robotic Control. IEEE Robotics Autom. Lett. Brian H. Yang, Dinesh Jayaraman, Glen Berseth, Alexei A. Efros, Sergey Levine
2020	J	`jnl`	Multi-agent Social Reinforcement Learning Improves Generalization. CoRR Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques
2020	Misc	`conf`	Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning. CoRL Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman
2020	J	`jnl`	OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. CoRR Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
2020	J	`jnl`	Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. CoRR Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer
2020	J	`jnl`	Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. CoRR Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine
2020	J	`jnl`	Offline Meta-Reinforcement Learning with Advantage Weighting. CoRR Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
2020	J	`jnl`	Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems. CoRR Sergey Levine, Aviral Kumar, George Tucker, Justin Fu
2020	J	`jnl`	OmniTact: A Multi-Directional High Resolution Touch Sensor. CoRR Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine
2020	A*	`conf`	OmniTact: A Multi-Directional High-Resolution Touch Sensor. ICRA Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine
2020	A*	`conf`	One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL. NeurIPS Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn
2020	J	`jnl`	One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL. CoRR Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn
2020	J	`jnl`	Parrot: Data-Driven Behavioral Priors for Reinforcement Learning. CoRR Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
2020	J	`jnl`	RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real. CoRR Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, Mohi Khansari
2020	A*	`conf`	RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real. CVPR Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, Mohi Khansari
2020	J	`jnl`	Rearrangement: A Challenge for Embodied AI. CoRR Dhruv Batra, Angel X. Chang, Sonia Chernova, Andrew J. Davison, Jia Deng, Vladlen Koltun, Sergey Levine, Jitendra Malik, Igor Mordatch, Roozbeh Mottaghi, Manolis Savva, Hao Su
2020	A*	`conf`	Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. ICLR Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
2020	Misc	`conf`	Reinforcement Learning with Videos: Combining Offline Observations with Interaction. CoRL Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn
2020	J	`jnl`	Reinforcement Learning with Videos: Combining Offline Observations with Interaction. CoRR Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn
2020	A*	`conf`	Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. NeurIPS Ben Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov
2020	J	`jnl`	Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. CoRR Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov
2020	A*	`conf`	SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards. ICLR Siddharth Reddy, Anca D. Dragan, Sergey Levine
2020	J	`jnl`	Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks. IEEE Robotics Autom. Lett. Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg
2020	A*	`conf`	Scalable Multi-Task Imitation Learning with Autonomous Improvement. ICRA Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn
2020	J	`jnl`	Scalable Multi-Task Imitation Learning with Autonomous Improvement. CoRR Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn
2020	A*	`conf`	Scaled Autonomy: Enabling Human Operators to Control Robot Fleets. ICRA Gokul Swamy, Siddharth Reddy, Sergey Levine, Anca D. Dragan
2020	J	`jnl`	Simple and Effective VAE Training with Calibrated Decoders. CoRR Oleh Rybkin, Kostas Daniilidis, Sergey Levine
2020	A*	`conf`	Skew-Fit: State-Covering Self-Supervised Reinforcement Learning. ICML Vitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine
2020	A*	`conf`	Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model. NeurIPS Alex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine
2020	A*	`conf`	TRASS: Time Reversal as Self-Supervision. ICRA Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, Vikash Kumar
2020	A*	`conf`	The Ingredients of Real World Robotic Reinforcement Learning. ICLR Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine
2020	J	`jnl`	The Ingredients of Real-World Robotic Reinforcement Learning. CoRR Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine
2020	A*	`conf`	The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. ICLR Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine
2020	J	`jnl`	The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. CoRR Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine
2020	A*	`conf`	Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. ICLR Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog
2020	J	`jnl`	Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. CoRR Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog
2020	A	`conf`	Unsupervised Reinforcement Learning. AAMAS Sergey Levine
2020	J	`jnl`	Unsupervised Sequence Forecasting of 100,000 Points for Unsupervised Trajectory Forecasting. CoRR Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart
2020	J	`jnl`	Variable-Shot Adaptation for Online Meta-Learning. CoRR Tianhe Yu, Xinyang Geng, Chelsea Finn, Sergey Levine
2020	J	`jnl`	ViNG: Learning Open-World Navigation with Visual Goals. CoRR Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine
2020	A*	`conf`	VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation. ICLR Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma
2020	J	`jnl`	WILDS: A Benchmark of in-the-Wild Distribution Shifts. CoRR Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
2020	A*	`conf`	Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards. ICLR Allan Zhou, Eric Jang, Daniel Kappler, Alexander Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn
2020	J	`jnl`	γ-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. CoRR Michael Janner, Igor Mordatch, Sergey Levine
2019	J	`jnl`	AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos. CoRR Laura Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine
2019	J	`jnl`	Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning. CoRR Xue Bin Peng, Aviral Kumar, Grace Zhang, Sergey Levine
2019	J	`jnl`	Adversarial Policies: Attacking Deep Reinforcement Learning. CoRR Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine, Stuart Russell
2019	J	`jnl`	Artificial Intelligence for Prosthetics - challenge solutions. CoRR Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hongsheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp
2019	—	`conf`	Automatically Composing Representation Transformations as a Means for Generalization. ICLR (Poster) Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths
2019	A*	`conf`	Causal Confusion in Imitation Learning. NeurIPS Pim de Haan, Dinesh Jayaraman, Sergey Levine
2019	J	`jnl`	Causal Confusion in Imitation Learning. CoRR Pim de Haan, Dinesh Jayaraman, Sergey Levine
2019	A*	`conf`	Compositional Plan Vectors. NeurIPS Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine
2019	Misc	`conf`	Contextual Imagined Goals for Self-Supervised Robotic Learning. CoRL Ashvin Nair, Shikhar Bahl, Alexander Khazatsky, Vitchyr Pong, Glen Berseth, Sergey Levine
2019	J	`jnl`	Contextual Imagined Goals for Self-Supervised Robotic Learning. CoRR Ashvin Nair, Shikhar Bahl, Alexander Khazatsky, Vitchyr Pong, Glen Berseth, Sergey Levine
2019	A*	`conf`	Data-efficient Learning of Morphology and Controller for a Microrobot. ICRA Thomas Liao, Grant Wang, Brian H. Yang, Rene Lee, Kristofer S. J. Pister, Sergey Levine, Roberto Calandra
2019	J	`jnl`	Data-efficient Learning of Morphology and Controller for a Microrobot. CoRR Thomas Liao, Grant Wang, Brian H. Yang, Rene Lee, Kristofer S. J. Pister, Sergey Levine, Roberto Calandra
2019	Misc	`conf`	Deep Dynamics Models for Learning Dexterous Manipulation. CoRL Anusha Nagabandi, Kurt Konolige, Sergey Levine, Vikash Kumar
2019	J	`jnl`	Deep Dynamics Models for Learning Dexterous Manipulation. CoRR Anusha Nagabandi, Kurt Konolige, Sergey Levine, Vikash Kumar
2019	—	`conf`	Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL. ICLR (Poster) Anusha Nagabandi, Chelsea Finn, Sergey Levine
2019	J	`jnl`	Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards. CoRR Gerrit Schoettler, Ashvin Nair, Jianlan Luo, Shikhar Bahl, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine
2019	A*	`conf`	Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. ICRA Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar
2019	A*	`conf`	Diagnosing Bottlenecks in Deep Q-learning Algorithms. ICML Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine
2019	J	`jnl`	Diagnosing Bottlenecks in Deep Q-learning Algorithms. CoRR Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine
2019	—	`conf`	Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning. ICLR (Poster) Ilya Kostrikov, Kumar Krishna Agrawal, Debidatta Dwibedi, Sergey Levine, Jonathan Tompson
2019	—	`conf`	Diversity is All You Need: Learning Skills without a Reward Function. ICLR (Poster) Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine
2019	J	`jnl`	Dynamical Distance Learning for Unsupervised and Semi-Supervised Skill Discovery. CoRR Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja, Sergey Levine
2019	J	`jnl`	Dynamics-Aware Unsupervised Discovery of Skills. CoRR Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman
2019	A*	`conf`	EMI: Exploration with Mutual Information. ICML HyoungSeok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song
2019	J	`jnl`	Efficient Exploration via State Marginal Matching. CoRR Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric P. Xing, Sergey Levine, Ruslan Salakhutdinov
2019	A*	`conf`	Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables. ICML Kate Rakelly, Aurick Zhou, Chelsea Finn, Sergey Levine, Deirdre Quillen
2019	J	`jnl`	Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables. CoRR Kate Rakelly, Aurick Zhou, Deirdre Quillen, Chelsea Finn, Sergey Levine
2019	—	`conf`	End-To-End Robotic Reinforcement Learning without Reward Engineering. Robotics: Science and Systems Avi Singh, Larry Yang, Chelsea Finn, Sergey Levine
2019	J	`jnl`	End-to-End Robotic Reinforcement Learning without Reward Engineering. CoRR Avi Singh, Larry Yang, Kristian Hartikainen, Chelsea Finn, Sergey Levine
2019	Misc	`conf`	Entity Abstraction in Visual Model-Based Reinforcement Learning. CoRL Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine
2019	J	`jnl`	Entity Abstraction in Visual Model-Based Reinforcement Learning. CoRR Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine
2019	J	`jnl`	Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations. CoRR Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg
2019	—	`conf`	From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following. ICLR (Poster) Justin Fu, Anoop Korattikara, Sergey Levine, Sergio Guadarrama
2019	J	`jnl`	From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following. CoRR Justin Fu, Anoop Korattikara, Sergey Levine, Sergio Guadarrama
2019	A*	`conf`	Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight. ICRA Katie Kang, Suneel Belkhale, Gregory Kahn, Pieter Abbeel, Sergey Levine
2019	J	`jnl`	Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight. CoRR Katie Kang, Suneel Belkhale, Gregory Kahn, Pieter Abbeel, Sergey Levine
2019	A*	`conf`	Guided Meta-Policy Search. NeurIPS Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn
2019	J	`jnl`	Guided Meta-Policy Search. CoRR Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn
2019	—	`conf`	Guiding Policies with Language via Meta-Learning. ICLR (Poster) John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine
2019	J	`jnl`	If MaxEnt RL is the Answer, What is the Question? CoRR Benjamin Eysenbach, Sergey Levine
2019	—	`conf`	Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight. Robotics: Science and Systems Annie Xie, Frederik Ebert, Sergey Levine, Chelsea Finn
2019	J	`jnl`	Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight. CoRR Annie Xie, Frederik Ebert, Sergey Levine, Chelsea Finn
2019	—	`conf`	InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine
2019	J	`jnl`	InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew M. Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio
2019	—	`conf`	Learning Actionable Representations with Goal Conditioned Policies. ICLR (Poster) Dibya Ghosh, Abhishek Gupta, Sergey Levine
2019	J	`jnl`	Learning Human Objectives by Evaluating Hypothetical Behavior. CoRR Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shane Legg, Jan Leike
2019	Misc	`conf`	Learning Latent Plans from Play. CoRL Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet
2019	J	`jnl`	Learning Latent Plans from Play. CoRR Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet
2019	J	`jnl`	Learning Powerful Policies by Using Consistent Dynamics Model. CoRR Shagun Sodhani, Anirudh Goyal, Tristan Deleu, Yoshua Bengio, Sergey Levine, Jian Tang
2019	J	`jnl`	Learning Predictive Models From Observation and Interaction. CoRR Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn
2019	J	`jnl`	Learning To Reach Goals Without Reinforcement Learning. CoRR Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine
2019	A*	`conf`	Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. ICML Kelvin Xu, Ellis Ratner, Anca D. Dragan, Sergey Levine, Chelsea Finn
2019	—	`conf`	Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning. ICLR (Poster) Anusha Nagabandi, Ignasi Clavera, Simin Liu, Ronald S. Fearing, Pieter Abbeel, Sergey Levine, Chelsea Finn
2019	A*	`conf`	Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching. ICRA Justin Lin, Roberto Calandra, Sergey Levine
2019	J	`jnl`	Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching. CoRR Justin Lin, Roberto Calandra, Sergey Levine
2019	—	`conf`	Learning to Walk Via Deep Reinforcement Learning. Robotics: Science and Systems Tuomas Haarnoja, Sehoon Ha, Aurick Zhou, Jie Tan, George Tucker, Sergey Levine
2019	J	`jnl`	Low Level Control of a Quadrotor with Deep Model-Based Reinforcement learning. CoRR Nathan O. Lambert, Daniel S. Drew, Joseph Yaconelli, Roberto Calandra, Sergey Levine, Kristofer S. J. Pister
2019	J	`jnl`	Low-Level Control of a Quadrotor With Deep Model-Based Reinforcement Learning. IEEE Robotics Autom. Lett. Nathan O. Lambert, Daniel S. Drew, Joseph Yaconelli, Sergey Levine, Roberto Calandra, Kristofer S. J. Pister
2019	A*	`conf`	MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies. NeurIPS Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine
2019	J	`jnl`	MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies. CoRR Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine
2019	A*	`conf`	Manipulation by Feel: Touch-Based Control with Deep Predictive Models. ICRA Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine
2019	J	`jnl`	Manipulation by Feel: Touch-Based Control with Deep Predictive Models. CoRR Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine
2019	A*	`conf`	Meta-Learning with Implicit Gradients. NeurIPS Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine
2019	J	`jnl`	Meta-Learning with Implicit Gradients. CoRR Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine
2019	J	`jnl`	Meta-Learning without Memorization. CoRR Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn
2019	Misc	`conf`	Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning. CoRL Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine
2019	J	`jnl`	Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning. CoRR Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine
2019	J	`jnl`	Model Inversion Networks for Model-Based Optimization. CoRR Aviral Kumar, Sergey Levine
2019	J	`jnl`	Model-Based Reinforcement Learning for Atari. CoRR Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H. Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Ryan Sepassi, George Tucker, Henryk Michalewski
2019	J	`jnl`	Morphology-Agnostic Visual Robotic Control. CoRR Brian H. Yang, Dinesh Jayaraman, Glen Berseth, Alexei A. Efros, Sergey Levine
2019	—	`conf`	Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. ICLR (Poster) Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2019	A*	`conf`	Off-Policy Evaluation via Off-Policy Classification. NeurIPS Alexander Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, Sergey Levine
2019	J	`jnl`	Off-Policy Evaluation via Off-Policy Classification. CoRR Alex Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, Sergey Levine
2019	A	`conf`	One-Shot Composition of Vision-Based Skills from Demonstration. IROS Tianhe Yu, Pieter Abbeel, Sergey Levine, Chelsea Finn
2019	A*	`conf`	Online Meta-Learning. ICML Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine
2019	J	`jnl`	Online Meta-Learning. CoRR Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine
2019	J	`jnl`	PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings. CoRR Nicholas Rhinehart, Rowan McAllister, Kris M. Kitani, Sergey Levine
2019	A*	`conf`	PRECOG: PREdiction Conditioned on Goals in Visual Multi-Agent Settings. ICCV Nicholas Rhinehart, Rowan McAllister, Kris Kitani, Sergey Levine
2019	J	`jnl`	Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control. CoRR Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine
2019	A*	`conf`	Planning with Goal-Conditioned Policies. NeurIPS Soroush Nasiriany, Vitchyr Pong, Steven Lin, Sergey Levine
2019	J	`jnl`	Planning with Goal-Conditioned Policies. CoRR Soroush Nasiriany, Vitchyr H. Pong, Steven Lin, Sergey Levine
2019	J	`jnl`	REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning. CoRR Brian H. Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman
2019	A*	`conf`	REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning. ICRA Brian H. Yang, Dinesh Jayaraman, Jesse Zhang, Sergey Levine
2019	Misc	`conf`	ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots. CoRL Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar
2019	J	`jnl`	ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots. CoRR Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar
2019	—	`conf`	Reasoning About Physical Interactions with Object-Oriented Prediction and Planning. ICLR (Poster) Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu
2019	—	`conf`	Recall Traces: Backtracking Models for Efficient Reinforcement Learning. ICLR (Poster) Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
2019	J	`jnl`	Recurrent Independent Mechanisms. CoRR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2019	J	`jnl`	Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. CoRR Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
2019	Misc	`conf`	Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning. CoRL Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, Karol Hausman
2019	J	`jnl`	Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning. CoRR Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, Karol Hausman
2019	A*	`conf`	Residual Reinforcement Learning for Robot Control. ICRA Tobias Johannink, Shikhar Bahl, Ashvin Nair, Jianlan Luo, Avinash Kumar, Matthias Loskyll, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine
2019	J	`jnl`	Reward-Conditioned Policies. CoRR Aviral Kumar, Xue Bin Peng, Sergey Levine
2019	Misc	`conf`	RoboNet: Large-Scale Multi-Robot Learning. CoRL Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn
2019	J	`jnl`	RoboNet: Large-Scale Multi-Robot Learning. CoRR Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn
2019	A*	`conf`	Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty. ICRA Rowan McAllister, Gregory Kahn, Jeff Clune, Sergey Levine
2019	J	`jnl`	SMiRL: Surprise Minimizing RL in Dynamic Environments. CoRR Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
2019	A*	`conf`	SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning. ICML Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine
2019	J	`jnl`	SQIL: Imitation Learning via Regularized Behavioral Cloning. CoRR Siddharth Reddy, Anca D. Dragan, Sergey Levine
2019	J	`jnl`	Scaled Autonomy: Enabling Human Operators to Control Robot Fleets. CoRR Gokul Swamy, Siddharth Reddy, Sergey Levine, Anca D. Dragan
2019	A*	`conf`	Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. NeurIPS Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2019	J	`jnl`	Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2019	A*	`conf`	Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks. CVPR Stephen James, Paul Wohlhart, Mrinal Kalakrishnan, Dmitry Kalashnikov, Alex Irpan, Julian Ibarz, Sergey Levine, Raia Hadsell, Konstantinos Bousmalis
2019	J	`jnl`	Skew-Fit: State-Covering Self-Supervised Reinforcement Learning. CoRR Vitchyr H. Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine
2019	A*	`conf`	Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction. NeurIPS Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, Sergey Levine
2019	J	`jnl`	Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction. CoRR Aviral Kumar, Justin Fu, George Tucker, Sergey Levine
2019	J	`jnl`	Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model. CoRR Alex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine
2019	—	`conf`	Time-Agnostic Prediction: Predicting Predictable Video Frames. ICLR (Poster) Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros, Sergey Levine
2019	A*	`conf`	Unsupervised Curricula for Visual Meta-Reinforcement Learning. NeurIPS Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn
2019	J	`jnl`	Unsupervised Curricula for Visual Meta-Reinforcement Learning. CoRR Allan Jabri, Kyle Hsu, Ben Eysenbach, Abhishek Gupta, Sergey Levine, Chelsea Finn
2019	—	`conf`	Unsupervised Learning via Meta-Learning. ICLR (Poster) Kyle Hsu, Sergey Levine, Chelsea Finn
2019	—	`conf`	Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow. ICLR (Poster) Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine
2019	J	`jnl`	VideoFlow: A Flow-Based Generative Model for Video. CoRR Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma
2019	A*	`conf`	Wasserstein Dependency Measure for Representation Learning. NeurIPS Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aäron van den Oord, Sergey Levine, Pierre Sermanet
2019	J	`jnl`	Wasserstein Dependency Measure for Representation Learning. CoRR Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aäron van den Oord, Sergey Levine, Pierre Sermanet
2019	J	`jnl`	Watch, Try, Learn: Meta-Learning from Demonstrations and Reward. CoRR Allan Zhou, Eric Jang, Daniel Kappler, Alexander Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn
2019	A*	`conf`	When to Trust Your Model: Model-Based Policy Optimization. NeurIPS Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine
2019	J	`jnl`	When to Trust Your Model: Model-Based Policy Optimization. CoRR Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine
2019	J	`jnl`	Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? CoRR Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine
2018	J	`jnl`	Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning. CoRR Ilya Kostrikov, Kumar Krishna Agrawal, Sergey Levine, Jonathan Tompson
2018	J	`jnl`	Automatically Composing Representation Transformations as a Means for Generalization. CoRR Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths
2018	Misc	`conf`	Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation. CoRL Gregory Kahn, Adam Villaflor, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation. CoRR Gregory Kahn, Adam Villaflor, Pieter Abbeel, Sergey Levine
2018	A*	`conf`	Composable Deep Reinforcement Learning for Robotic Manipulation. ICRA Tuomas Haarnoja, Vitchyr Pong, Aurick Zhou, Murtaza Dalal, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Composable Deep Reinforcement Learning for Robotic Manipulation. CoRR Tuomas Haarnoja, Vitchyr Pong, Aurick Zhou, Murtaza Dalal, Pieter Abbeel, Sergey Levine
2018	—	`conf`	Conditional Networks for Few-Shot Semantic Segmentation. ICLR (Workshop) Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alyosha A. Efros, Sergey Levine
2018	A*	`conf`	Data-Efficient Hierarchical Reinforcement Learning. NeurIPS Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	J	`jnl`	Data-Efficient Hierarchical Reinforcement Learning. CoRR Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	J	`jnl`	Deep Imitative Models for Flexible Inference, Planning, and Control. CoRR Nicholas Rhinehart, Rowan McAllister, Sergey Levine
2018	A*	`conf`	Deep Object-Centric Representations for Generalizable Robot Learning. ICRA Coline Devin, Pieter Abbeel, Trevor Darrell, Sergey Levine
2018	J	`jnl`	Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL. CoRR Anusha Nagabandi, Chelsea Finn, Sergey Levine
2018	A*	`conf`	Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. ICRA Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine
2018	J	`jnl`	Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. CoRR Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine
2018	A*	`conf`	Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models. NeurIPS Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine
2018	J	`jnl`	Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models. CoRR Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine
2018	J	`jnl`	DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills. CoRR Xue Bin Peng, Pieter Abbeel, Sergey Levine, Michiel van de Panne
2018	J	`jnl`	DeepMimic: example-guided deep reinforcement learning of physics-based character skills. ACM Trans. Graph. Xue Bin Peng, Pieter Abbeel, Sergey Levine, Michiel van de Panne
2018	J	`jnl`	Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. CoRR Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar
2018	J	`jnl`	Diversity is All You Need: Learning Skills without a Reward Function. CoRR Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine
2018	—	`conf`	Divide-and-Conquer Reinforcement Learning. ICLR (Poster) Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
2018	J	`jnl`	EMI: Exploration with Mutual Information Maximizing State and Action Embeddings. CoRR HyoungSeok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song
2018	Misc	`conf`	Few-Shot Goal Inference for Visuomotor Learning and Planning. CoRL Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Few-Shot Goal Inference for Visuomotor Learning and Planning. CoRR Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Few-Shot Segmentation Propagation with Guided Networks. CoRR Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alexei A. Efros, Sergey Levine
2018	Misc	`conf`	Grasp2Vec: Learning Object Representations from Self-Supervised Grasping. CoRL Eric Jang, Coline Devin, Vincent Vanhoucke, Sergey Levine
2018	J	`jnl`	Grasp2Vec: Learning Object Representations from Self-Supervised Grasping. CoRR Eric Jang, Coline Devin, Vincent Vanhoucke, Sergey Levine
2018	J	`jnl`	Guiding Policies with Language via Meta-Learning. CoRR John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, John DeNero, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Hierarchical Policy Design for Sample-Efficient Learning of Robot Table Tennis Through Self-Play. CoRR Reza Mahjourian, Navdeep Jaitly, Nevena Lazic, Sergey Levine, Risto Miikkulainen
2018	A*	`conf`	Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation. ICRA Yuxuan Liu, Abhishek Gupta, Pieter Abbeel, Sergey Levine
2018	A*	`conf`	Latent Space Policies for Hierarchical Reinforcement Learning. ICML Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Latent Space Policies for Hierarchical Reinforcement Learning. CoRR Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Learning Actionable Representations with Goal-Conditioned Policies. CoRR Dibya Ghosh, Abhishek Gupta, Sergey Levine
2018	—	`conf`	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. Robotics: Science and Systems Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov, Sergey Levine
2018	J	`jnl`	Learning Flexible and Reusable Locomotion Primitives for a Microrobot. CoRR Brian H. Yang, Grant Wang, Roberto Calandra, Daniel Contreras, Sergey Levine, Kristofer S. J. Pister
2018	J	`jnl`	Learning Flexible and Reusable Locomotion Primitives for a Microrobot. IEEE Robotics Autom. Lett. Brian H. Yang, Grant Wang, Roberto Calandra, Daniel Contreras, Sergey Levine, Kristofer S. J. Pister
2018	A	`conf`	Learning Image-Conditioned Dynamics Models for Control of Underactuated Legged Millirobots. IROS Anusha Nagabandi, Guangzhao Yang, Thomas Asmar, Ravi Pandya, Gregory Kahn, Sergey Levine, Ronald S. Fearing
2018	—	`conf`	Learning Instance Segmentation by Interaction. CVPR Workshops Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik
2018	J	`jnl`	Learning Instance Segmentation by Interaction. CoRR Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik
2018	—	`conf`	Learning Robust Rewards with Adverserial Inverse Reinforcement Learning. ICLR (Poster) Justin Fu, Katie Luo, Sergey Levine
2018	J	`jnl`	Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. CoRR Kelvin Xu, Ellis Ratner, Anca D. Dragan, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection. Int. J. Robotics Res. Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, Deirdre Quillen
2018	J	`jnl`	Learning to Adapt: Meta-Learning for Model-Based Control. CoRR Ignasi Clavera, Anusha Nagabandi, Ronald S. Fearing, Pieter Abbeel, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. CoRR Lukasz Kidzinski, Sharada Prasanna Mohanty, Carmichael F. Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis, Zhibo Chen, Zhizheng Zhang, Jiale Chen, Jun Shi, Zhuobin Zheng, Chun Yuan, Zhihui Lin, Henryk Michalewski, Piotr Milos, Blazej Osinski, Andrew Melnik, Malte Schilling, Helge J. Ritter, Sean F. Carroll, Jennifer L. Hicks, Sergey Levine, Marcel Salathé, Scott L. Delp
2018	J	`jnl`	Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning. CoRR Lukasz Kidzinski, Sharada P. Mohanty, Carmichael F. Ong, Jennifer L. Hicks, Sean F. Carroll, Sergey Levine, Marcel Salathé, Scott L. Delp
2018	J	`jnl`	Learning to Walk via Deep Reinforcement Learning. CoRR Tuomas Haarnoja, Aurick Zhou, Sehoon Ha, Jie Tan, George Tucker, Sergey Levine
2018	—	`conf`	Learning with Latent Language. NAACL-HLT Jacob Andreas, Dan Klein, Sergey Levine
2018	—	`conf`	Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. ICLR (Poster) Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine
2018	—	`conf`	Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm. ICLR (Poster) Chelsea Finn, Sergey Levine
2018	A*	`conf`	Meta-Reinforcement Learning of Structured Exploration Strategies. NeurIPS Abhishek Gupta, Russell Mendonca, Yuxuan Liu, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Meta-Reinforcement Learning of Structured Exploration Strategies. CoRR Abhishek Gupta, Russell Mendonca, Yuxuan Liu, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning. CoRR Vladimir Feinberg, Alvin Wan, Ion Stoica, Michael I. Jordan, Joseph E. Gonzalez, Sergey Levine
2018	J	`jnl`	More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch. IEEE Robotics Autom. Lett. Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine
2018	J	`jnl`	More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch. CoRR Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine
2018	J	`jnl`	Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. CoRR Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	A*	`conf`	Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning. ICRA Anusha Nagabandi, Gregory Kahn, Ronald S. Fearing, Sergey Levine
2018	J	`jnl`	One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks. CoRR Tianhe Yu, Pieter Abbeel, Sergey Levine, Chelsea Finn
2018	—	`conf`	One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning. ICLR (Workshop) Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2018	—	`conf`	One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning. Robotics: Science and Systems Tianhe Yu, Chelsea Finn, Sudeep Dasari, Annie Xie, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning. CoRR Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2018	A*	`conf`	Probabilistic Model-Agnostic Meta-Learning. NeurIPS Chelsea Finn, Kelvin Xu, Sergey Levine
2018	J	`jnl`	Probabilistic Model-Agnostic Meta-Learning. CoRR Chelsea Finn, Kelvin Xu, Sergey Levine
2018	J	`jnl`	QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. CoRR Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, Sergey Levine
2018	J	`jnl`	Reasoning About Physical Interactions with Object-Oriented Prediction and Planning. CoRR Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu
2018	J	`jnl`	Recall Traces: Backtracking Models for Efficient Reinforcement Learning. CoRR Anirudh Goyal, Philemon Brakel, William Fedus, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
2018	—	`conf`	Recasting Gradient-Based Meta-Learning as Hierarchical Bayes. ICLR (Poster) Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas L. Griffiths
2018	J	`jnl`	Recasting Gradient-Based Meta-Learning as Hierarchical Bayes. CoRR Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas L. Griffiths
2018	—	`conf`	Regret Minimization for Partially Observable Deep Reinforcement Learning. ICLR (Workshop) Peter H. Jin, Sergey Levine, Kurt Keutzer
2018	A*	`conf`	Regret Minimization for Partially Observable Deep Reinforcement Learning. ICML Peter H. Jin, Kurt Keutzer, Sergey Levine
2018	J	`jnl`	Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review. CoRR Sergey Levine
2018	—	`conf`	Reinforcement Learning from Imperfect Demonstrations. ICLR (Workshop) Yang Gao, Huazhe Xu, Ji Lin, Fisher Yu, Sergey Levine, Trevor Darrell
2018	J	`jnl`	Reinforcement Learning from Imperfect Demonstrations. CoRR Yang Gao, Huazhe Xu, Ji Lin, Fisher Yu, Sergey Levine, Trevor Darrell
2018	J	`jnl`	Residual Reinforcement Learning for Robot Control. CoRR Tobias Johannink, Shikhar Bahl, Ashvin Nair, Jianlan Luo, Avinash Kumar, Matthias Loskyll, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine
2018	J	`jnl`	Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty. CoRR Rowan McAllister, Gregory Kahn, Jeff Clune, Sergey Levine
2018	Misc	`conf`	Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning. CoRL Frederik Ebert, Sudeep Dasari, Alex X. Lee, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning. CoRR Frederik Ebert, Sudeep Dasari, Alex X. Lee, Sergey Levine, Chelsea Finn
2018	J	`jnl`	SFV: Reinforcement Learning of Physical Skills from Videos. CoRR Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	SFV: reinforcement learning of physical skills from videos. ACM Trans. Graph. Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning. CoRR Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine
2018	Misc	`conf`	Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. CoRL Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, Sergey Levine
2018	A*	`conf`	Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. ICML John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. CoRR John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine
2018	A*	`conf`	Self-Supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation. ICRA Gregory Kahn, Adam Villaflor, Bosen Ding, Pieter Abbeel, Sergey Levine
2018	—	`conf`	Shared Autonomy via Deep Reinforcement Learning. Robotics: Science and Systems Siddharth Reddy, Anca D. Dragan, Sergey Levine
2018	J	`jnl`	Shared Autonomy via Deep Reinforcement Learning. CoRR Siddharth Reddy, Sergey Levine, Anca D. Dragan
2018	J	`jnl`	Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks. CoRR Stephen James, Paul Wohlhart, Mrinal Kalakrishnan, Dmitry Kalashnikov, Alex Irpan, Julian Ibarz, Sergey Levine, Raia Hadsell, Konstantinos Bousmalis
2018	A*	`conf`	Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control. CVPR Fereshteh Sadeghi, Alexander Toshev, Eric Jang, Sergey Levine
2018	J	`jnl`	Soft Actor-Critic Algorithms and Applications. CoRR Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, Sergey Levine
2018	A*	`conf`	Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor. ICML Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor. CoRR Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Stochastic Adversarial Video Prediction. CoRR Alex X. Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, Sergey Levine
2018	—	`conf`	Stochastic Variational Video Prediction. ICLR (Poster) Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine
2018	—	`conf`	Temporal Difference Models: Model-Free Deep RL for Model-Based Control. ICLR (Poster) Vitchyr Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine
2018	J	`jnl`	Temporal Difference Models: Model-Free Deep RL for Model-Based Control. CoRR Vitchyr Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine
2018	—	`conf`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. ICLR (Workshop) George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	A*	`conf`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. ICML George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	J	`jnl`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. CoRR George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	J	`jnl`	Time Reversal as Self-Supervision. CoRR Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, Vikash Kumar
2018	J	`jnl`	Time-Agnostic Prediction: Predicting Predictable Video Frames. CoRR Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros, Sergey Levine
2018	A*	`conf`	Time-Contrastive Networks: Self-Supervised Learning from Video. ICRA Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine
2018	J	`jnl`	Universal Planning Networks. CoRR Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn
2018	A*	`conf`	Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control. ICML Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Unsupervised Learning via Meta-Learning. CoRR Kyle Hsu, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Unsupervised Meta-Learning for Reinforcement Learning. CoRR Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn, Sergey Levine
2018	A*	`conf`	Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping. ICRA 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	J	`jnl`	Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow. CoRR Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine
2018	A*	`conf`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. NeurIPS Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2018	J	`jnl`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. CoRR Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2018	A*	`conf`	Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-to-End Learning from Demonstration. ICRA Rouhollah Rahmatizadeh, Pooya Abolghasemi, Ladislau Bölöni, Sergey Levine
2018	J	`jnl`	Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control. CoRR Frederik Ebert, Chelsea Finn, Sudeep Dasari, Annie Xie, Alex X. Lee, Sergey Levine
2018	A*	`conf`	Visual Memory for Robust Path Following. NeurIPS Ashish Kumar, Saurabh Gupta, David F. Fouhey, Sergey Levine, Jitendra Malik
2018	J	`jnl`	Visual Memory for Robust Path Following. CoRR Ashish Kumar, Saurabh Gupta, David F. Fouhey, Sergey Levine, Jitendra Malik
2018	A*	`conf`	Visual Reinforcement Learning with Imagined Goals. NeurIPS Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine
2018	J	`jnl`	Visual Reinforcement Learning with Imagined Goals. CoRR Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine
2018	A*	`conf`	Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior. NeurIPS Siddharth Reddy, Anca D. Dragan, Sergey Levine
2018	J	`jnl`	Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior. CoRR Siddharth Reddy, Anca D. Dragan, Sergey Levine
2017	—	`conf`	CAD2RL: Real Single-Image Flight Without a Single Real Image. Robotics: Science and Systems Fereshteh Sadeghi, Sergey Levine
2017	A*	`conf`	Cognitive Mapping and Planning for Visual Navigation. CVPR Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, Jitendra Malik
2017	J	`jnl`	Cognitive Mapping and Planning for Visual Navigation. CoRR Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, Jitendra Malik
2017	A	`conf`	Collective robot reinforcement learning with distributed asynchronous guided policy search. IROS Ali Yahya, Adrian Li, Mrinal Kalakrishnan, Yevgen Chebotar, Sergey Levine
2017	A*	`conf`	Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning. ICML Yevgen Chebotar, Karol Hausman, Marvin Zhang, Gaurav S. Sukhatme, Stefan Schaal, Sergey Levine
2017	J	`jnl`	Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning. CoRR Yevgen Chebotar, Karol Hausman, Marvin Zhang, Gaurav S. Sukhatme, Stefan Schaal, Sergey Levine
2017	J	`jnl`	Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation. CoRR Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine
2017	A*	`conf`	Combining self-supervised learning and imitation for vision-based rope manipulation. ICRA Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine
2017	J	`jnl`	Deep Object-Centric Representations for Generalizable Robot Learning. CoRR Coline Devin, Pieter Abbeel, Trevor Darrell, Sergey Levine
2017	A*	`conf`	Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates. ICRA Shixiang Gu, Ethan Holly, Timothy P. Lillicrap, Sergey Levine
2017	A*	`conf`	Deep reinforcement learning for tensegrity robot locomotion. ICRA Marvin Zhang, Xinyang Geng, Jonathan Bruce, Ken Caluwaerts, Massimo Vespignani, Vytas SunSpiral, Pieter Abbeel, Sergey Levine
2017	A*	`conf`	Deep visual foresight for planning robot motion. ICRA Chelsea Finn, Sergey Levine
2017	J	`jnl`	Divide-and-Conquer Reinforcement Learning. CoRR Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
2017	—	`conf`	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. ICLR (Poster) Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran, Sergey Levine
2017	—	`conf`	EX2: Exploration with Exemplar Models for Deep Reinforcement Learning. NIPS Justin Fu, John D. Co-Reyes, Sergey Levine
2017	J	`jnl`	EX2: Exploration with Exemplar Models for Deep Reinforcement Learning. CoRR Justin Fu, John D. Co-Reyes, Sergey Levine
2017	Misc	`conf`	End-to-End Learning of Semantic Grasping. CoRL Eric Jang, Sudheendra Vijayanarasimhan, Peter Pastor, Julian Ibarz, Sergey Levine
2017	J	`jnl`	End-to-End Learning of Semantic Grasping. CoRR Eric Jang, Sudheendra Vijayanarasimhan, Peter Pastor, Julian Ibarz, Sergey Levine
2017	A*	`conf`	GPLAC: Generalizing Vision-Based Robotic Skills Using Weakly Labeled Images. ICCV Avi Singh, Larry Yang, Sergey Levine
2017	J	`jnl`	GPLAC: Generalizing Vision-Based Robotic Skills using Weakly Labeled Images. CoRR Avi Singh, Larry Yang, Sergey Levine
2017	—	`conf`	Generalizing Skills with Semi-Supervised Reinforcement Learning. ICLR (Poster) Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Goal-Driven Dynamics Learning via Bayesian Optimization. CoRR Somil Bansal, Roberto Calandra, Ted Xiao, Sergey Levine, Claire J. Tomlin
2017	—	`conf`	Goal-driven dynamics learning via Bayesian optimization. CDC Somil Bansal, Roberto Calandra, Ted Xiao, Sergey Levine, Claire J. Tomlin
2017	J	`jnl`	Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation. CoRR Yuxuan Liu, Abhishek Gupta, Pieter Abbeel, Sergey Levine
2017	—	`conf`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. NIPS Shixiang Gu, Tim Lillicrap, Richard E. Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine
2017	J	`jnl`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. CoRR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Bernhard Schölkopf, Sergey Levine
2017	J	`jnl`	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. CoRR Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, John Schulman, Emanuel Todorov, Sergey Levine
2017	—	`conf`	Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning. ICLR (Poster) Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning. CoRR Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine
2017	Misc	`conf`	Learning Robotic Manipulation of Granular Media. CoRL Connor Schenck, Jonathan Tompson, Sergey Levine, Dieter Fox
2017	J	`jnl`	Learning Robotic Manipulation of Granular Media. CoRR Connor Schenck, Jonathan Tompson, Dieter Fox, Sergey Levine
2017	J	`jnl`	Learning Robust Rewards with Adversarial Inverse Reinforcement Learning. CoRR Justin Fu, Katie Luo, Sergey Levine
2017	—	`conf`	Learning Visual Servoing with Deep Features and Fitted Q-Iteration. ICLR (Poster) Alex X. Lee, Sergey Levine, Pieter Abbeel
2017	J	`jnl`	Learning Visual Servoing with Deep Features and Fitted Q-Iteration. CoRR Alex X. Lee, Sergey Levine, Pieter Abbeel
2017	A*	`conf`	Learning from the hindsight plan - Episodic MPC improvement. ICRA Aviv Tamar, Garrett Thomas, Tianhao Zhang, Sergey Levine, Pieter Abbeel
2017	A*	`conf`	Learning modular neural network policies for multi-task and multi-robot transfer. ICRA Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Learning with Latent Language. CoRR Jacob Andreas, Dan Klein, Sergey Levine
2017	J	`jnl`	Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. CoRR Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine
2017	J	`jnl`	MBMF: Model-Based Priors for Model-Free Reinforcement Learning. CoRR Somil Bansal, Roberto Calandra, Sergey Levine, Claire J. Tomlin
2017	J	`jnl`	Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm. CoRR Chelsea Finn, Sergey Levine
2017	A*	`conf`	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. ICML Chelsea Finn, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. CoRR Chelsea Finn, Pieter Abbeel, Sergey Levine
2017	A*	`conf`	Modular Multitask Reinforcement Learning with Policy Sketches. ICML Jacob Andreas, Dan Klein, Sergey Levine
2017	J	`jnl`	Neural Network Dynamics Models for Control of Under-actuated Legged Millirobots. CoRR Anusha Nagabandi, Guangzhao Yang, Thomas Asmar, Gregory Kahn, Sergey Levine, Ronald S. Fearing
2017	J	`jnl`	Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning. CoRR Anusha Nagabandi, Gregory Kahn, Ronald S. Fearing, Sergey Levine
2017	Misc	`conf`	One-Shot Visual Imitation Learning via Meta-Learning. CoRL Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	One-Shot Visual Imitation Learning via Meta-Learning. CoRR Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2017	A*	`conf`	PLATO: Policy learning using adaptive trajectory optimization. ICRA Gregory Kahn, Tianhao Zhang, Sergey Levine, Pieter Abbeel
2017	A*	`conf`	Path integral guided policy search. ICRA Yevgen Chebotar, Mrinal Kalakrishnan, Ali Yahya, Adrian Li, Stefan Schaal, Sergey Levine
2017	—	`conf`	Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic. ICLR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
2017	J	`jnl`	Regret Minimization for Partially Observable Deep Reinforcement Learning. CoRR Peter H. Jin, Sergey Levine, Kurt Keutzer
2017	A*	`conf`	Reinforcement Learning with Deep Energy-Based Policies. ICML Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Reinforcement Learning with Deep Energy-Based Policies. CoRR Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine
2017	A*	`conf`	Reset-free guided policy search: Efficient deep reinforcement learning with stochastic initial states. ICRA William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine
2017	Misc	`conf`	Self-Supervised Visual Planning with Temporal Skip Connections. CoRL Frederik Ebert, Chelsea Finn, Alex X. Lee, Sergey Levine
2017	J	`jnl`	Self-Supervised Visual Planning with Temporal Skip Connections. CoRR Frederik Ebert, Chelsea Finn, Alex X. Lee, Sergey Levine
2017	J	`jnl`	Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation. CoRR Gregory Kahn, Adam Villaflor, Bosen Ding, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Sim2Real View Invariant Visual Servoing by Recurrent Control. CoRR Fereshteh Sadeghi, Alexander Toshev, Eric Jang, Sergey Levine
2017	J	`jnl`	Stochastic Variational Video Prediction. CoRR Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine
2017	Misc	`conf`	The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes? CoRL Roberto Calandra, Andrew Owens, Manu Upadhyaya, Wenzhen Yuan, Justin Lin, Edward H. Adelson, Sergey Levine
2017	J	`jnl`	The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes? CoRR Roberto Calandra, Andrew Owens, Manu Upadhyaya, Wenzhen Yuan, Justin Lin, Edward H. Adelson, Sergey Levine
2017	J	`jnl`	Time-Contrastive Networks: Self-Supervised Learning from Multi-View Observation. CoRR Pierre Sermanet, Corey Lynch, Jasmine Hsu, Sergey Levine
2017	—	`conf`	Time-Contrastive Networks: Self-Supervised Learning from Multi-view Observation. CVPR Workshops Pierre Sermanet, Corey Lynch, Jasmine Hsu, Sergey Levine
2017	J	`jnl`	Uncertainty-Aware Reinforcement Learning for Collision Avoidance. CoRR Gregory Kahn, Adam Villaflor, Vitchyr Pong, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Unifying Map and Landmark Based Representations for Visual Navigation. CoRR Saurabh Gupta, David F. Fouhey, Sergey Levine, Jitendra Malik
2017	—	`conf`	Unsupervised Perceptual Rewards for Imitation Learning. ICLR (Workshop) Pierre Sermanet, Kelvin Xu, Sergey Levine
2017	—	`conf`	Unsupervised Perceptual Rewards for Imitation Learning. Robotics: Science and Systems Pierre Sermanet, Kelvin Xu, Sergey Levine
2017	J	`jnl`	Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping. CoRR Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, Yunfei Bai, Matthew Kelcey, Mrinal Kalakrishnan, Laura Downs, Julian Ibarz, Peter Pastor, Kurt Konolige, Sergey Levine, Vincent Vanhoucke
2017	A*	`conf`	Value Iteration Networks. IJCAI Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel
2017	J	`jnl`	Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration. CoRR Rouhollah Rahmatizadeh, Pooya Abolghasemi, Ladislau Bölöni, Sergey Levine
2016	J	`jnl`	(CAD)$^2$RL: Real Single-Image Flight without a Single Real Image. CoRR Fereshteh Sadeghi, Sergey Levine
2016	J	`jnl`	A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models. CoRR Chelsea Finn, Paul F. Christiano, Pieter Abbeel, Sergey Levine
2016	C	`conf`	Adapting Deep Visuomotor Representations with Weak Pairwise Constraints. WAFR Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell
2016	—	`conf`	Backprop KF: Learning Discriminative Deterministic State Estimators. NIPS Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Backprop KF: Learning Discriminative Deterministic State Estimators. CoRR Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search. CoRR Ali Yahya, Adrian Li, Mrinal Kalakrishnan, Yevgen Chebotar, Sergey Levine
2016	A*	`conf`	Continuous Deep Q-Learning with Model-based Acceleration. ICML Shixiang Gu, Timothy P. Lillicrap, Ilya Sutskever, Sergey Levine
2016	J	`jnl`	Continuous Deep Q-Learning with Model-based Acceleration. CoRR Shixiang Gu, Timothy P. Lillicrap, Ilya Sutskever, Sergey Levine
2016	J	`jnl`	Deep Reinforcement Learning for Robotic Manipulation. CoRR Shixiang Gu, Ethan Holly, Timothy P. Lillicrap, Sergey Levine
2016	J	`jnl`	Deep Reinforcement Learning for Tensegrity Robot Locomotion. CoRR Xinyang Geng, Marvin Zhang, Jonathan Bruce, Ken Caluwaerts, Massimo Vespignani, Vytas SunSpiral, Pieter Abbeel, Sergey Levine
2016	J	`jnl`	Deep Visual Foresight for Planning Robot Motion. CoRR Chelsea Finn, Sergey Levine
2016	A*	`conf`	Deep spatial autoencoders for visuomotor learning. ICRA Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. CoRR Aravind Rajeswaran, Sarvjeet Ghotra, Sergey Levine, Balaraman Ravindran
2016	J	`jnl`	End-to-End Training of Deep Visuomotor Policies. J. Mach. Learn. Res. Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel
2016	J	`jnl`	Generalizing Skills with Semi-Supervised Reinforcement Learning. CoRR Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine
2016	A*	`conf`	Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization. ICML Chelsea Finn, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization. CoRR Chelsea Finn, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Guided Policy Search as Approximate Mirror Descent. CoRR William Montgomery, Sergey Levine
2016	—	`conf`	Guided Policy Search via Approximate Mirror Descent. NIPS William H. Montgomery, Sergey Levine
2016	A*	`conf`	High-Dimensional Continuous Control Using Generalized Advantage Estimation. ICLR (Poster) John Schulman, Philipp Moritz, Sergey Levine, Michael I. Jordan, Pieter Abbeel
2016	J	`jnl`	Learning Dexterous Manipulation Policies from Experience and Imitation. CoRR Vikash Kumar, Abhishek Gupta, Emanuel Todorov, Sergey Levine
2016	J	`jnl`	Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration. CoRR Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection. CoRR Sergey Levine, Peter Pastor, Alex Krizhevsky, Deirdre Quillen
2016	—	`conf`	Learning Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection. ISER Sergey Levine, Peter Pastor, Alex Krizhevsky, Deirdre Quillen
2016	J	`jnl`	Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer. CoRR Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine
2016	A*	`conf`	Learning Visual Predictive Models of Physics for Playing Billiards. ICLR (Poster) Katerina Fragkiadaki, Pulkit Agrawal, Sergey Levine, Jitendra Malik
2016	A*	`conf`	Learning deep control policies for autonomous aerial vehicles with MPC-guided policy search. ICRA Tianhao Zhang, Gregory Kahn, Sergey Levine, Pieter Abbeel
2016	A*	`conf`	Learning deep neural network policies with continuous memory states. ICRA Marvin Zhang, Zoe McCarthy, Chelsea Finn, Sergey Levine, Pieter Abbeel
2016	A	`conf`	Learning dexterous manipulation for a soft robotic hand from human demonstrations. IROS Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Learning from the Hindsight Plan - Episodic MPC Improvement. CoRR Aviv Tamar, Garrett Thomas, Tianhao Zhang, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Learning to Poke by Poking: Experiential Learning of Intuitive Physics. CoRR Pulkit Agrawal, Ashvin Nair, Pieter Abbeel, Jitendra Malik, Sergey Levine
2016	A*	`conf`	Model-based reinforcement learning with parametrized physical models and optimism-driven exploration. ICRA Chris Xie, Sachin Patil, Teodor Mihai Moldovan, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Modular Multitask Reinforcement Learning with Policy Sketches. CoRR Jacob Andreas, Dan Klein, Sergey Levine
2016	A*	`conf`	MuProp: Unbiased Backpropagation for Stochastic Neural Networks. ICLR (Poster) Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih
2016	A	`conf`	One-shot learning of manipulation skills with online dynamics adaptation and neural network priors. IROS Justin Fu, Sergey Levine, Pieter Abbeel
2016	A*	`conf`	Optimal control with learned local models: Application to dexterous manipulation. ICRA Vikash Kumar, Emanuel Todorov, Sergey Levine
2016	J	`jnl`	PLATO: Policy Learning using Adaptive Trajectory Optimization. CoRR Gregory Kahn, Tianhao Zhang, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Path Integral Guided Policy Search. CoRR Yevgen Chebotar, Mrinal Kalakrishnan, Ali Yahya, Adrian Li, Stefan Schaal, Sergey Levine
2016	J	`jnl`	Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic. CoRR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
2016	J	`jnl`	Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States. CoRR William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine
2016	—	`conf`	Unsupervised Learning for Physical Interaction through Video Prediction. NIPS Chelsea Finn, Ian J. Goodfellow, Sergey Levine
2016	J	`jnl`	Unsupervised Learning for Physical Interaction through Video Prediction. CoRR Chelsea Finn, Ian J. Goodfellow, Sergey Levine
2016	J	`jnl`	Unsupervised Perceptual Rewards for Imitation Learning. CoRR Pierre Sermanet, Kelvin Xu, Sergey Levine
2016	—	`conf`	Value Iteration Networks. NIPS Aviv Tamar, Sergey Levine, Pieter Abbeel, Yi Wu, Garrett Thomas
2016	J	`jnl`	Value Iteration Networks. CoRR Aviv Tamar, Sergey Levine, Pieter Abbeel
2015	J	`jnl`	End-to-End Training of Deep Visuomotor Policies. CoRR Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel
2015	J	`jnl`	Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models. CoRR Bradly C. Stadie, Sergey Levine, Pieter Abbeel
2015	J	`jnl`	Learning Contact-Rich Manipulation Skills with Guided Policy Search. CoRR Sergey Levine, Nolan Wagener, Pieter Abbeel
2015	J	`jnl`	Learning Deep Control Policies for Autonomous Aerial Vehicles with MPC-Guided Policy Search. CoRR Tianhao Zhang, Gregory Kahn, Sergey Levine, Pieter Abbeel
2015	J	`jnl`	Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders. CoRR Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, Pieter Abbeel
2015	A	`conf`	Learning compound multi-step controllers under unknown dynamics. IROS Weiqiao Han, Sergey Levine, Pieter Abbeel
2015	A*	`conf`	Learning contact-rich manipulation skills with guided policy search. ICRA Sergey Levine, Nolan Wagener, Pieter Abbeel
2015	A*	`conf`	Learning force-based manipulation of deformable objects from multiple demonstrations. ICRA Alex X. Lee, Henry Lu, Abhishek Gupta, Sergey Levine, Pieter Abbeel
2015	A	`conf`	Learning from multiple demonstrations using trajectory-aware non-rigid registration with applications to deformable object manipulation. IROS Alex X. Lee, Abhishek Gupta, Henry Lu, Sergey Levine, Pieter Abbeel
2015	J	`jnl`	Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration. CoRR Christopher Xie, Sachin Patil, Teodor Mihai Moldovan, Sergey Levine, Pieter Abbeel
2015	J	`jnl`	One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors. CoRR Justin Fu, Sergey Levine, Pieter Abbeel
2015	A*	`conf`	Optimism-driven exploration for nonlinear systems. ICRA Teodor Mihai Moldovan, Sergey Levine, Michael I. Jordan, Pieter Abbeel
2015	J	`jnl`	Policy Learning with Continuous Memory States for Partially Observed Robotic Control. CoRR Marvin Zhang, Sergey Levine, Zoe McCarthy, Chelsea Finn, Pieter Abbeel
2015	A*	`conf`	Recurrent Network Models for Human Dynamics. ICCV Katerina Fragkiadaki, Sergey Levine, Panna Felsen, Jitendra Malik
2015	J	`jnl`	Recurrent Network Models for Kinematic Tracking. CoRR Katerina Fragkiadaki, Sergey Levine, Jitendra Malik
2015	J	`jnl`	Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. CoRR Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Xingchao Peng, Sergey Levine, Kate Saenko, Trevor Darrell
2015	A*	`conf`	Trust Region Policy Optimization. ICML John Schulman, Sergey Levine, Pieter Abbeel, Michael I. Jordan, Philipp Moritz
2015	J	`jnl`	Trust Region Policy Optimization. CoRR John Schulman, Sergey Levine, Philipp Moritz, Michael I. Jordan, Pieter Abbeel
2014	A*	`conf`	Learning Complex Neural Network Policies with Trajectory Optimization. ICML Sergey Levine, Vladlen Koltun
2014	—	`conf`	Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics. NIPS Sergey Levine, Pieter Abbeel
2014	—	`—`	Motor skill learning with local trajectory methods. Sergey Levine
2014	A	`conf`	Offline policy evaluation across representations with applications to educational games. AAMAS Travis Mandel, Yun-En Liu, Sergey Levine, Emma Brunskill, Zoran Popovic
2013	J	`jnl`	Exploring Deep and Recurrent Architectures for Optimal Control. CoRR Sergey Levine
2013	—	`conf`	Guided Policy Search. ICML (3) Sergey Levine, Vladlen Koltun
2013	—	`conf`	Variational Policy Search via Trajectory Optimization. NIPS Sergey Levine, Vladlen Koltun
2012	J	`jnl`	Continuous Inverse Optimal Control with Locally Optimal Examples CoRR Sergey Levine, Vladlen Koltun
2012	A*	`conf`	Continuous Inverse Optimal Control with Locally Optimal Examples. ICML Sergey Levine, Vladlen Koltun
2012	J	`jnl`	Continuous character control with low-dimensional embeddings. ACM Trans. Graph. Sergey Levine, Jack M. Wang, Alexis Haraux, Zoran Popovic, Vladlen Koltun
2012	—	`conf`	Physically Plausible Simulation for Character Animation. Symposium on Computer Animation Sergey Levine, Jovan Popovic
2011	—	`conf`	Nonlinear Inverse Reinforcement Learning with Gaussian Processes. NIPS Sergey Levine, Zoran Popovic, Vladlen Koltun
2011	J	`jnl`	Space-time planning with parameterized locomotion controllers. ACM Trans. Graph. Sergey Levine, Yongjoon Lee, Vladlen Koltun, Zoran Popovic
2010	—	`conf`	Feature Construction for Inverse Reinforcement Learning. NIPS Sergey Levine, Zoran Popovic, Vladlen Koltun
2010	J	`jnl`	Gesture controllers. ACM Trans. Graph. Sergey Levine, Philipp Krähenbühl, Sebastian Thrun, Vladlen Koltun
2009	J	`jnl`	Real-time prosody-driven synthesis of body language. ACM Trans. Graph. Sergey Levine, Christian Theobalt, Vladlen Koltun