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| Do as i can, not as i say: Grounding language in robotic affordances M Ahn, A Brohan, N Brown, Y Chebotar, O Cortes, B David, C Finn, C Fu, ... arXiv preprint arXiv:2204.01691, 2022 | 1783* | 2022 |
| Palm-e: An embodied multimodal language model D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ... arXiv preprint arXiv:2303.03378, 2023 | 1409 | 2023 |
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| Socratic models: Composing zero-shot multimodal reasoning with language A Zeng, M Attarian, B Ichter, K Choromanski, A Wong, S Welker, ... arXiv preprint arXiv:2204.00598, 2022 | 515 | 2022 |
| Learning sampling distributions for robot motion planning B Ichter, J Harrison, M Pavone arXiv preprint arXiv:1709.05448, 2018 | 418 | 2018 |
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| Deterministic sampling-based motion planning: Optimality, complexity, and performance L Janson, B Ichter, M Pavone The International Journal of Robotics Research 37 (1), 46-61, 2018 | 174 | 2018 |
| Learning language-conditioned robot behavior from offline data and crowd-sourced annotation S Nair, E Mitchell, K Chen, B Ichter, S Savarese, C Finn Conference on Robot Learning, 1303-1315, 2022 | 153 | 2022 |
| Large language models as general pattern machines S Mirchandani, F Xia, P Florence, B Ichter, D Driess, MG Arenas, K Rao, ... arXiv preprint arXiv:2307.04721, 2023 | 147 | 2023 |
| Scaling robot learning with semantically imagined experience T Yu, T Xiao, A Stone, J Tompson, A Brohan, S Wang, J Singh, C Tan, ... arXiv preprint arXiv:2302.11550, 2023 | 117* | 2023 |
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Fei XiaResearch Scientist, Google DeepMind在 google.com 的电子邮件经过验证