| Learning modular neural network policies for multi-task and multi-robot transfer C Devin, A Gupta, T Darrell, P Abbeel, S Levine 2017 IEEE international conference on robotics and automation (ICRA), 2169-2176, 2017 | 449 | 2017 |
| Learning invariant feature spaces to transfer skills with reinforcement learning A Gupta, C Devin, YX Liu, P Abbeel, S Levine arXiv preprint arXiv:1703.02949, 2017 | 343 | 2017 |
| Open x-embodiment: Robotic learning datasets and rt-x models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023 | 202 | 2023 |
| Learning to reach goals via iterated supervised learning D Ghosh, A Gupta, A Reddy, J Fu, C Devin, B Eysenbach, S Levine arXiv preprint arXiv:1912.06088, 2019 | 163 | 2019 |
| Adapting deep visuomotor representations with weak pairwise constraints E Tzeng, C Devin, J Hoffman, C Finn, P Abbeel, S Levine, K Saenko, ... arXiv preprint arXiv:1511.07111, 2015 | 162* | 2015 |
| Grasp2vec: Learning object representations from self-supervised grasping E Jang, C Devin, V Vanhoucke, S Levine arXiv preprint arXiv:1811.06964, 2018 | 131 | 2018 |
| Deep object-centric policies for autonomous driving D Wang, C Devin, QZ Cai, F Yu, T Darrell 2019 International Conference on Robotics and Automation (ICRA), 8853-8859, 2019 | 128 | 2019 |
| Towards adapting deep visuomotor representations from simulated to real environments E Tzeng, C Devin, J Hoffman, C Finn, X Peng, S Levine, K Saenko, ... arXiv preprint arXiv:1511.07111 2 (3), 2015 | 120 | 2015 |
| Deep object-centric representations for generalizable robot learning C Devin, P Abbeel, T Darrell, S Levine 2018 IEEE International Conference on Robotics and Automation (ICRA), 7111-7118, 2018 | 108 | 2018 |
| Beyond pick-and-place: Tackling robotic stacking of diverse shapes AX Lee, CM Devin, Y Zhou, T Lampe, K Bousmalis, JT Springenberg, ... 5th Annual Conference on Robot Learning, 2021 | 95 | 2021 |
| Monocular plan view networks for autonomous driving D Wang, C Devin, QZ Cai, P Krähenbühl, T Darrell 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 88 | 2019 |
| Embedding word similarity with neural machine translation F Hill, K Cho, S Jean, C Devin, Y Bengio arXiv preprint arXiv:1412.6448, 2014 | 67 | 2014 |
| Robocat: A self-improving foundation agent for robotic manipulation K Bousmalis, G Vezzani, D Rao, C Devin, AX Lee, M Bauza, T Davchev, ... arXiv preprint arXiv:2306.11706, 2023 | 66 | 2023 |
| Not all neural embeddings are born equal F Hill, KH Cho, S Jean, C Devin, Y Bengio arXiv preprint arXiv:1410.0718, 2014 | 54 | 2014 |
| Smirl: Surprise minimizing reinforcement learning in unstable environments G Berseth, D Geng, C Devin, N Rhinehart, C Finn, D Jayaraman, S Levine arXiv preprint arXiv:1912.05510, 2019 | 51 | 2019 |
| Fully autonomous real-world reinforcement learning with applications to mobile manipulation C Sun, J Orbik, CM Devin, BH Yang, A Gupta, G Berseth, S Levine Conference on Robot Learning, 308-319, 2022 | 45 | 2022 |
| Open X-Embodiment: Robotic learning datasets and RT-X models OXE Collaboration, A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, ... arXiv preprint arXiv:2310.08864, 2023 | 40 | 2023 |
| Modular networks for compositional instruction following R Corona, D Fried, C Devin, D Klein, T Darrell arXiv preprint arXiv:2010.12764, 2020 | 33 | 2020 |
| Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control C Devin, D Geng, P Abbeel, T Darrell, S Levine Advances in Neural Information Processing Systems, 14989-15000, 2019 | 29* | 2019 |
| Learning to reach goals without reinforcement learning D Ghosh, A Gupta, J Fu, A Reddy, C Devin, B Eysenbach, S Levine | 28 | 2019 |
