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Modern machine learning systems rely on large datasets to attain broad generalization, and this often poses a challenge in robot learning, where each robotic platform and task might have only a small dataset.
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K. Kang, G. Kahn, and S. Levine · 2021
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Language conditioned imitation learning over unstructured data
C. Lynch and P. Sermanet · 2021
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Hydra: Hybrid robot actions for imitation learning
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Interactive language: Talking to robots in real time
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Furniturebench: Reproducible real-world benchmark for long-horizon complex manipulation
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MUTEX: Learning unified policies from multimodal task specifications
R. Shah, R. Martín-Martín, and Y. Zhu · 2023
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Train offline, test online: A real robot learning benchmark, 2023
G. Zhou, V. Dean, M. K. Srirama, A. Rajeswaran, J. Pari, K. Hatch, A. Jain, T. Yu, P. Abbeel, L. Pinto, C. Finn, and A. Gupta · 2023
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Robot learning on the job: Human-in-the-loop autonomy and learning during deployment
H. Liu, S. Nasiriany, L. Zhang, Z. Bao, and Y. Zhu · 2023
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S. Saxena, M. Sharma, and O. Kroemer · 2023
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CLVR jaco play dataset, 2023
S. Dass, J. Yapeter, J. Zhang, J. Zhang, K. Pertsch, S. Nikolaidis, and J. J. Lim · 2023
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Multi-stage cable routing through hierarchical imitation learning
J. Luo, C. Xu, X. Geng, G. Feng, K. Fang, L. Tan, S. Schaal, and S. Levine · 2023
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Structured world models from human videos
R. Mendonca, S. Bahl, and D. Pathak · 2023
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Gpt-4 technical report, 2024
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Octo: An open-source generalist robot policy
Octo Model Team, D. Ghosh, H. Walke, K. Pertsch, K. Black, O. Mees, S. Dasari, J. Hejna, C. Xu, J. Luo, T. Kreiman, Y. Tan, P. Sanketi, Q. Vuong, T. Xiao, D. Sadigh, C. Finn, and S. Levine · 2024
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Pushing the limits of cross-embodiment learning for manipulation and navigation
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Droid: A large-scale in-the-wild robot manipulation dataset
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