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Vision-Language-Action (VLA) models offer a pivotal approach to learning robotic manipulation at scale by repurposing large pre-trained Vision-Language-Models (VLM) to output robotic actions.
Language models are few-shot learners, 2020
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Rt-1: Robotics transformer for real-world control at scale
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Curious exploration via structured world models yields zero-shot object manipulation
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Lora: Low-rank adaptation of large language models
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Motif: Intrinsic motivation from artificial intelligence feedback, 2023
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Rt-2: Vision-language-action models transfer web knowledge to robotic control, 2023
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Rt-2: Vision-language-action models transfer web knowledge to robotic control
B. Zitkovich, T. Yu, S. Xu, P. Xu, T. Xiao, F. Xia, J. Wu, P. Wohlhart, S. Welker, A. Wahid, et al · 2023
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Vision-language foundation models as effective robot imitators
X. Li, M. Liu, H. Zhang, C. Yu, J. Xu, H. Wu, C. Cheang, Y. Jing, W. Zhang, H. Liu, et al · 2023
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Focus: Object-centric world models for robotics manipulation
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An investigation into pre-training object-centric representations for reinforcement learning
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Dinov2: Learning robust visual features without supervision
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Pytorch fsdp: Experiences on scaling fully sharded data parallel, 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
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Bridgedata v2: A dataset for robot learning at scale
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Sam 2: Segment anything in images and videos
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Libero: Benchmarking knowledge transfer for lifelong robot learning
B. Liu, Y. Zhu, C. Gao, Y. Feng, Q. Liu, Y. Zhu, and P. Stone · 2023
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Paligemma: A versatile 3b vlm for transfer, 2024
L. Beyer, A. Steiner, A. S. Pinto, A. Kolesnikov, X. Wang, D. Salz, M. Neumann, I. Alabdulmohsin, M. Tschannen, E. Bugliarello, T. Unterthiner, D. Keysers, S. Koppula, F. Liu, A. Grycner, A. Gritsenko, N. Houlsby, M. Kumar, K. Rong, J. Eisenschlos, R. Kabra, M. Bauer, M. Bošnjak, X. Chen, M. Minderer, P. Voigtlaender, I. Bica, I. Balazevic, J. Puigcerver, P. Papalampidi, O. Henaff, X. Xiong, R. Soricut, J. Harmsen, and X. Zhai · 2024
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Cambrian-1: A fully open, vision-centric exploration of multimodal llms, 2024
S. Tong, E. Brown, P. Wu, S. Woo, M. Middepogu, S. C. Akula, J. Yang, S. Yang, A. Iyer, X. Pan, Z. Wang, R. Fergus, Y. LeCun, and S. Xie · 2024
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Openvla: An open-source vision-language-action model
M. J. Kim, K. Pertsch, S. Karamcheti, T. Xiao, A. Balakrishna, S. Nair, R. Rafailov, E. Foster, G. Lam, P. Sanketi, et al · 2024
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Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0
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Octo: An open-source generalist robot policy
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Jack of all trades, master of some, a multi-purpose transformer agent
Q. Gallouédec, E. Beeching, C. Romac, and E. Dellandréa · 2024
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openvla-7b-prismatic
M. J. Kim, K. Pertsch, S. Karamcheti, T. Xiao, A. Balakrishna, S. Nair, R. Rafailov, E. Foster, G. Lam, P. Sanketi, et al · 2024
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Prismatic vlms: Investigating the design space of visually-conditioned language models, 2024
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Paligemma: A versatile 3b vlm for transfer, 2024
L. Beyer, A. Steiner, A. S. Pinto, A. Kolesnikov, X. Wang, D. Salz, M. Neumann, I. Alabdulmohsin, M. Tschannen, E. Bugliarello, T. Unterthiner, D. Keysers, S. Koppula, F. Liu, A. Grycner, A. Gritsenko, N. Houlsby, M. Kumar, K. Rong, J. Eisenschlos, R. Kabra, M. Bauer, M. Bošnjak, X. Chen, M. Minderer, P. Voigtlaender, I. Bica, I. Balazevic, J. Puigcerver, P. Papalampidi, O. Henaff, X. Xiong, R. Soricut, J. Harmsen, and X. Zhai · 2024
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π \pi 0: A vision-language-action flow model for general robot control, 2024
K. Black, N. Brown, D. Driess, A. Esmail, M. Equi, C. Finn, N. Fusai, L. Groom, K. Hausman, B. Ichter, et al · 2025
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Spatialvla: Exploring spatial representations for visual-language-action model
D. Qu, H. Song, Q. Chen, Y. Yao, X. Ye, Y. Ding, Z. Wang, J. Gu, B. Zhao, D. Wang, et al · 2025
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Objectvla: End-to-end open-world object manipulation without demonstration
M. Zhu, Y. Zhu, J. Li, Z. Zhou, J. Wen, X. Liu, C. Shen, Y. Peng, and F. Feng · 2025
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Llara: Supercharging robot learning data for vision-language policy
X. Li, C. Mata, J. Park, K. Kahatapitiya, Y. S. Jang, J. Shang, K. Ranasinghe, R. Burgert, M. Cai, Y. J. Lee, and M. S. Ryoo · 2025
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Fine-tuning vision-language-action models: Optimizing speed and success
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Efficient diffusion transformer policies with mixture of expert denoisers for multitask learning
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Tinyvla: Toward fast, data-efficient vision-language-action models for robotic manipulation
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Fast: Efficient action tokenization for vision-language-action models
K. Pertsch, K. Stachowicz, B. Ichter, D. Driess, S. Nair, Q. Vuong, O. Mees, C. Finn, and S. Levine · 2025
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Dexgraspvla: A vision-language-action framework towards general dexterous grasping, 2025
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Controlmanip: Few-shot manipulation fine-tuning via object-centric conditional control
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