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2020 – today
- 2024
[j24]Rafael Rafailov, Kyle Beltran Hatch, Anikait Singh, Aviral Kumar, Laura M. Smith, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Sergey Levine, Chelsea Finn:
D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. RLJ 5: 2178-2197 (2024)- [j23]Noriaki Hirose
, Dhruv Shah, Ajay Sridhar, Sergey Levine:
SACSoN: Scalable Autonomous Control for Social Navigation. IEEE Robotics Autom. Lett. 9(1): 49-56 (2024) - [j22]Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, Sergey Levine:
Multistage Cable Routing Through Hierarchical Imitation Learning. IEEE Trans. Robotics 40: 1476-1491 (2024) - [c402]Kuba Grudzien Kuba, Masatoshi Uehara, Sergey Levine, Pieter Abbeel:
Functional Graphical Models: Structure Enables Offline Data-Driven Optimization. AISTATS 2024: 2449-2457 - [c401]Marwa Abdulhai, Micah Carroll, Justin Svegliato, Anca D. Dragan, Sergey Levine:
Defining Deception in Decision Making. AAMAS 2024: 2111-2113 - [c400]Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine:
Training Diffusion Models with Reinforcement Learning. ICLR 2024 - [c399]Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Rich Walke, Chelsea Finn, Aviral Kumar, Sergey Levine:
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models. ICLR 2024 - [c398]Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn:
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features. ICLR 2024 - [c397]Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song:
The False Promise of Imitating Proprietary Language Models. ICLR 2024 - [c396]Joey Hong, Anca D. Dragan, Sergey Levine:
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. ICLR 2024 - [c395]Katie Kang, Amrith Setlur, Claire J. Tomlin, Sergey Levine:
Deep Neural Networks Tend To Extrapolate Predictably. ICLR 2024 - [c394]Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine:
RLIF: Interactive Imitation Learning as Reinforcement Learning. ICLR 2024 - [c393]Seohong Park, Oleh Rybkin, Sergey Levine:
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction. ICLR 2024 - [c392]Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine:
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data. ICLR 2024 - [c391]Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter:
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. ICML 2024 - [c390]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:
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. ICML 2024 - [c389]Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine:
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings. ICML 2024 - [c388]Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach:
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. ICML 2024 - [c387]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:
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. ICML 2024 - [c386]Seohong Park, Tobias Kreiman, Sergey Levine:
Foundation Policies with Hilbert Representations. ICML 2024 - [c385]Amrith Setlur, Saurabh Garg, Virginia Smith, Sergey Levine:
Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models. ICML 2024 - [c384]Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani:
Feedback Efficient Online Fine-Tuning of Diffusion Models. ICML 2024 - [c383]Annie Xie, Logan M. Bhamidipaty, Evan Zheran Liu, Joey Hong, Sergey Levine, Chelsea Finn:
Learning to Explore in POMDPs with Informational Rewards. ICML 2024 - [c382]Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar:
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL. ICML 2024 - [c381]Ajay Sridhar, Dhruv Shah, Catherine Glossop, Sergey Levine:
NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration. ICRA 2024: 63-70 - [c380]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 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 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, 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:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 2024: 6892-6903 - [c379]Laura M. Smith, Yunhao Cao, Sergey Levine:
Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion. ICRA 2024: 10829-10836 - [c378]Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine:
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. ICRA 2024: 16961-16969 - [c377]Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar:
Robotic Offline RL from Internet Videos via Value-Function Learning. ICRA 2024: 16977-16984 - [i486]Jakub Grudzien Kuba, Masatoshi Uehara, Pieter Abbeel, Sergey Levine:
Functional Graphical Models: Structure Enables Offline Data-Driven Optimization. CoRR abs/2401.05442 (2024) - [i485]Jianlan Luo, Charles Xu, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine:
FMB: a Functional Manipulation Benchmark for Generalizable Robotic Learning. CoRR abs/2401.08553 (2024) - [i484]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:
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents. CoRR abs/2401.12963 (2024) - [i483]Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine:
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. CoRR abs/2401.16013 (2024) - [i482]Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath:
Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control. CoRR abs/2401.16889 (2024) - [i481]William Chen, Oier Mees, Aviral Kumar, Sergey Levine:
Vision-Language Models Provide Promptable Representations for Reinforcement Learning. CoRR abs/2402.02651 (2024) - [i480]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:
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. CoRR abs/2402.07872 (2024) - [i479]Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Tommaso Biancalani, Sergey Levine:
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control. CoRR abs/2402.15194 (2024) - [i478]Seohong Park, Tobias Kreiman, Sergey Levine:
Foundation Policies with Hilbert Representations. CoRR abs/2402.15567 (2024) - [i477]Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani:
Feedback Efficient Online Fine-Tuning of Diffusion Models. CoRR abs/2402.16359 (2024) - [i476]Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine:
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings. CoRR abs/2402.17135 (2024) - [i475]Jonathan Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah, Quan Vuong, Chelsea Finn, Dorsa Sadigh, Sergey Levine:
Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation. CoRR abs/2402.19432 (2024) - [i474]Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar:
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL. CoRR abs/2402.19446 (2024) - [i473]Noriaki Hirose, Dhruv Shah, Kyle Stachowicz, Ajay Sridhar, Sergey Levine:
SELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation. CoRR abs/2403.00991 (2024) - [i472]Fangchen Liu, Kuan Fang, Pieter Abbeel, Sergey Levine:
MOKA: Open-Vocabulary Robotic Manipulation through Mark-Based Visual Prompting. CoRR abs/2403.03174 (2024) - [i471]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:
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. CoRR abs/2403.03950 (2024) - [i470]Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine:
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. CoRR abs/2403.04082 (2024) - [i469]Katie Kang, Eric Wallace, Claire J. Tomlin, Aviral Kumar, Sergey Levine:
Unfamiliar Finetuning Examples Control How Language Models Hallucinate. CoRR abs/2403.05612 (2024) - [i468]Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn:
Yell At Your Robot: Improving On-the-Fly from Language Corrections. CoRR abs/2403.12910 (2024) - [i467]Jiayi Pan, Yichi Zhang, Nicholas Tomlin, Yifei Zhou, Sergey Levine, Alane Suhr:
Autonomous Evaluation and Refinement of Digital Agents. CoRR abs/2404.06474 (2024) - [i466]Toru Lin, Yu Zhang, Qiyang Li, Haozhi Qi, Brent Yi, Sergey Levine, Jitendra Malik:
Learning Visuotactile Skills with Two Multifingered Hands. CoRR abs/2404.16823 (2024) - [i465]Kyle Stachowicz, Sergey Levine:
RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes. CoRR abs/2405.04714 (2024) - [i464]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:
Evaluating Real-World Robot Manipulation Policies in Simulation. CoRR abs/2405.05941 (2024) - [i463]Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine:
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. CoRR abs/2405.10292 (2024) - [i462]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:
Octo: An Open-Source Generalist Robot Policy. CoRR abs/2405.12213 (2024) - [i461]Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani:
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models. CoRR abs/2405.19673 (2024) - [i460]Yutaka Shimizu, Joey Hong, Sergey Levine, Masayoshi Tomizuka:
Strategically Conservative Q-Learning. CoRR abs/2406.04534 (2024) - [i459]Seungeun Rho, Laura M. Smith, Tianyu Li, Sergey Levine, Xue Bin Peng, Sehoon Ha:
Language Guided Skill Discovery. CoRR abs/2406.06615 (2024) - [i458]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:
OpenVLA: An Open-Source Vision-Language-Action Model. CoRR abs/2406.09246 (2024) - [i457]Seohong Park, Kevin Frans, Sergey Levine, Aviral Kumar:
Is Value Learning Really the Main Bottleneck in Offline RL? CoRR abs/2406.09329 (2024) - [i456]Hao Bai, Yifei Zhou, Mert Cemri, Jiayi Pan, Alane Suhr, Sergey Levine, Aviral Kumar:
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning. CoRR abs/2406.11896 (2024) - [i455]Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali:
Adding Conditional Control to Diffusion Models with Reinforcement Learning. CoRR abs/2406.12120 (2024) - [i454]Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach:
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. CoRR abs/2406.17098 (2024) - [i453]Annie S. Chen, Alec M. Lessing, Andy Tang, Govind Chada, Laura M. Smith, Sergey Levine, Chelsea Finn:
Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models. CoRR abs/2407.02666 (2024) - [i452]Xiaoyu Huang, Qiayuan Liao, Yiming Ni, Zhongyu Li, Laura M. Smith, Sergey Levine, Xue Bin Peng, Koushil Sreenath:
HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation. CoRR abs/2407.06584 (2024) - [i451]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:
Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. CoRR abs/2407.07775 (2024) - [i450]Michal Zawalski, William Chen, Karl Pertsch, Oier Mees, Chelsea Finn, Sergey Levine:
Robotic Control via Embodied Chain-of-Thought Reasoning. CoRR abs/2407.08693 (2024) - [i449]Manan Tomar, Philippe Hansen-Estruch, Philip Bachman, Alex Lamb, John Langford, Matthew E. Taylor, Sergey Levine:
Video Occupancy Models. CoRR abs/2407.09533 (2024) - [i448]Masatoshi Uehara, Yulai Zhao, Tommaso Biancalani, Sergey Levine:
Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review. CoRR abs/2407.13734 (2024) - [i447]Zhiyuan Zhou, Pranav Atreya, Abraham Lee, Homer Walke, Oier Mees, Sergey Levine:
Autonomous Improvement of Instruction Following Skills via Foundation Models. CoRR abs/2407.20635 (2024) - [i446]Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Aviv Regev, Sergey Levine, Masatoshi Uehara:
Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding. CoRR abs/2408.08252 (2024) - [i445]Rafael Rafailov, Kyle Hatch, Anikait Singh, Laura M. Smith, Aviral Kumar, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Chelsea Finn, Sergey Levine:
D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. CoRR abs/2408.08441 (2024) - [i444]Ria Doshi, Homer Walke, Oier Mees, Sudeep Dasari, Sergey Levine:
Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation. CoRR abs/2408.11812 (2024) - [i443]Junsu Kim, Seohong Park, Sergey Levine:
Unsupervised-to-Online Reinforcement Learning. CoRR abs/2408.14785 (2024) - [i442]Vivek Myers, Bill Chunyuan Zheng, Oier Mees, Sergey Levine, Kuan Fang:
Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation. CoRR abs/2408.16228 (2024) - [i441]Grace Tang, Swetha Rajkumar, Yifei Zhou, Homer Rich Walke, Sergey Levine, Kuan Fang:
KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data. CoRR abs/2409.14066 (2024) - [i440]Noriaki Hirose, Catherine Glossop, Ajay Sridhar, Dhruv Shah, Oier Mees, Sergey Levine:
LeLaN: Learning A Language-Conditioned Navigation Policy from In-the-Wild Videos. CoRR abs/2410.03603 (2024) - [i439]Sudeep Dasari, Oier Mees, Sebastian Zhao, Mohan Kumar Srirama, Sergey Levine:
The Ingredients for Robotic Diffusion Transformers. CoRR abs/2410.10088 (2024) - [i438]Hongbo Zhang, Zhongyu Li, Xuanqi Zeng, Laura M. Smith, Kyle Stachowicz, Dhruv Shah, Linzhu Yue, Zhitao Song, Weipeng Xia, Sergey Levine, Koushil Sreenath, Yun-hui Liu:
Traversability-Aware Legged Navigation by Learning from Real-World Visual Data. CoRR abs/2410.10621 (2024) - [i437]Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel:
One Step Diffusion via Shortcut Models. CoRR abs/2410.12557 (2024) - [i436]Jakub Grudzien Kuba, Pieter Abbeel, Sergey Levine:
Cliqueformer: Model-Based Optimization with Structured Transformers. CoRR abs/2410.13106 (2024) - [i435]Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Hanchen Wang, Aviv Regev:
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design. CoRR abs/2410.13643 (2024) - [i434]Mitsuhiko Nakamoto, Oier Mees, Aviral Kumar, Sergey Levine:
Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance. CoRR abs/2410.13816 (2024) - [i433]Max Wilcoxson, Qiyang Li, Kevin Frans, Sergey Levine:
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration. CoRR abs/2410.18076 (2024) - [i432]Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine, Alexei A. Efros:
Prioritized Generative Replay. CoRR abs/2410.18082 (2024) - [i431]Kyle Beltran Hatch, Ashwin Balakrishna, Oier Mees, Suraj Nair, Seohong Park, Blake Wulfe, Masha Itkina, Benjamin Eysenbach, Sergey Levine, Thomas Kollar, Benjamin Burchfiel:
GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. CoRR abs/2410.20018 (2024) - [i430]Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine:
OGBench: Benchmarking Offline Goal-Conditioned RL. CoRR abs/2410.20092 (2024) - [i429]Jianlan Luo, Charles Xu, Jeffrey Wu, Sergey Levine:
Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning. CoRR abs/2410.21845 (2024) - [i428]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:
π0: A Vision-Language-Action Flow Model for General Robot Control. CoRR abs/2410.24164 (2024) - 2023
- [j21]Shagun Sodhani, Sergey Levine, Amy Zhang:
Improving Generalization with Approximate Factored Value Functions. Trans. Mach. Learn. Res. 2023 (2023) - [c376]Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine:
ViNT: A Foundation Model for Visual Navigation. CoRL 2023: 711-733 - [c375]Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine:
Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning. CoRL 2023: 1348-1361 - [c374]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:
BridgeData V2: A Dataset for Robot Learning at Scale. CoRL 2023: 1723-1736 - [c373]Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine:
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. CoRL 2023: 1930-1949 - [c372]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:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRL 2023: 2165-2183 - [c371]Dhruv Shah, Michael Robert Equi, Blazej Osinski, Fei Xia, Brian Ichter, Sergey Levine:
Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning. CoRL 2023: 2683-2699 - [c370]Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine:
FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing. CoRL 2023: 3100-3111 - [c369]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:
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL 2023: 3894-3908 - [c368]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:
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRL 2023: 3909-3928 - [c367]Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang:
Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. ICLR 2023 - [c366]Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov:
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. ICLR 2023 - [c365]Joey Hong, Aviral Kumar, Sergey Levine:
Confidence-Conditioned Value Functions for Offline Reinforcement Learning. ICLR 2023 - [c364]Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine:
Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes. ICLR 2023 - [c363]