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Generalist imitation learning policies trained on large datasets show great promise for solving diverse manipulation tasks.
Scaling data-driven robotics with reward sketching and batch reinforcement learning, 2020
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Multiple interactions made easy (mime): Large scale demonstrations data for imitation
P. Sharma, L. Mohan, L. Pinto, and A. Gupta · 2018
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Scalable deep reinforcement learning for vision-based robotic manipulation
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Language models are few-shot learners
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Scaling laws for neural language models
J. Kaplan, S. McCandlish, T. Henighan, T. B. Brown, B. Chess, R. Child, S. Gray, A. Radford, J. Wu, and D. Amodei · 2020
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Learning transferable visual models from natural language supervision
A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark, G. Krueger, and I. Sutskever · 2021
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Training compute-optimal large language models, 2022
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Scaling vision transformers
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Eliciting compatible demonstrations for multi-human imitation learning, 2022
K. Gandhi, S. Karamcheti, M. Liao, and D. Sadigh · 2022
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Rt-2: Vision-language-action models transfer web knowledge to robotic control, 2023
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Doremi: Optimizing data mixtures speeds up language model pretraining
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Universal manipulation interface: In-the-wild robot teaching without in-the-wild robots, 2024
C. Chi, Z. Xu, C. Pan, E. Cousineau, B. Burchfiel, S. Feng, R. Tedrake, and S. Song · 2024
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Efficient data collection for robotic manipulation via compositional generalization, 2024
J. Gao, A. Xie, T. Xiao, C. Finn, and D. Sadigh · 2024
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Benchmarking vision, language, & action models on robotic learning tasks, 2024
P. Guruprasad, H. Sikka, J. Song, Y. Wang, and P. P. Liang · 2024
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Re-mix: Optimizing data mixtures for large scale imitation learning, 2024
J. Hejna, C. Bhateja, Y. Jian, K. Pertsch, and D. Sadigh · 2024
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Scalable diffusion models with transformers
W. Peebles and S. Xie · 2023
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Data quality in imitation learning, 2023
S. Belkhale, Y. Cui, and D. Sadigh · 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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No, to the right: Online language corrections for robotic manipulation via shared autonomy
Y. Cui, S. Karamcheti, R. Palleti, N. Shivakumar, P. Liang, and D. Sadigh · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
C. Chi, S. Feng, Y. Du, Z. Xu, E. Cousineau, B. Burchfiel, and S. Song · 2023
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Behavior retrieval: Few-shot imitation learning by querying unlabeled datasets
M. Du, S. Nair, D. Sadigh, and C. Finn · 2023
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π 0 \pi_{0} : A vision-language-action flow model for general robot control, 2024
K. Black et al · 2024
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OpenAI et al · 2024
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The llama 3 herd of models, 2024
A. Grattafiori et al · 2024
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Data scaling laws in imitation learning for robotic manipulation, 2024
F. Lin, Y. Hu, P. Sheng, C. Wen, J. You, and Y. Gao · 2024
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Maniskill3: Gpu parallelized robotics simulation and rendering for generalizable embodied ai
S. Tao, F. Xiang, A. Shukla, Y. Qin, X. Hinrichsen, X. Yuan, C. Bao, X. Lin, Y. Liu, T. kai Chan, Y. Gao, X. Li, T. Mu, N. Xiao, A. Gurha, Z. Huang, R. Calandra, R. Chen, S. Luo, and H. Su · 2024
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On the effectiveness of retrieval, alignment, and replay in manipulation
N. Di Palo and E. Johns · 2024
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Gemini robotics: Bringing ai into the physical world, 2025
G. R. Team et al · 2025
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Fine-tuning vision-language-action models: Optimizing speed and success, 2025
M. J. Kim, C. Finn, and P. Liang · 2025
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Mini-batch coresets for memory-efficient language model training on data mixtures, 2025
D. Nguyen, W. Yang, R. Anand, Y. Yang, and B. Mirzasoleiman · 2025
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Robot data curation with mutual information estimators, 2025
J. Hejna, S. Mirchandani, A. Balakrishna, A. Xie, A. Wahid, J. Tompson, P. Sanketi, D. Shah, C. Devin, and D. Sadigh · 2025
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Regmix: Data mixture as regression for language model pre-training, 2025
Q. Liu, X. Zheng, N. Muennighoff, G. Zeng, L. Dou, T. Pang, J. Jiang, and M. Lin · 2025
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Efficient Evaluation of Multi-Task Robot Policies With Active Experiment Selection, Feb. 2025
A. Anwar, R. Gupta, Z. Merchant, S. Ghosh, W. Neiswanger, and J. Thomason · 2025
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Predictive red teaming: Breaking policies without breaking robots, 2025
A. Majumdar, M. Sharma, D. Kalashnikov, S. Singh, P. Sermanet, and V. Sindhwani · 2025
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Demogen: Synthetic demonstration generation for data-efficient visuomotor policy learning
Z. Xue, S. Deng, Z. Chen, Y. Wang, Z. Yuan, and H. Xu · 2025
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