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Vision-language-action models have gained significant attention for their ability to model multimodal sequences in embodied instruction following tasks.
Deep residual learning for image recognition
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Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
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Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch. 2021 · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby. 2021 · 2021
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Implicit behavioral cloning
Pete Florence, Corey Lynch, Andy Zeng, Oscar A. Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, and Jonathan Tompson. 2021 · 2021
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Offline reinforcement learning as one big sequence modeling problem
Michael Janner, Qiyang Li, and Sergey Levine. 2021 · 2021
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M6: A chinese multimodal pretrainer
Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, and 6 others. 2021 · 2021
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Predicting autism spectrum disorder from brain imaging data by graph convolutional network
Yueen Ma, Da Yan, Cheng Long, D. Rangaprakash, and Gopikrishna Deshpande. 2021 · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021 · 2021
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Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob L. Menick, Sebastian Borgeaud, and 8 others. 2022 · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross B. Girshick. 2022 · 2022
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Do as I can, not as I say: Grounding language in robotic affordances
Brian Ichter, Anthony Brohan, Yevgen Chebotar, Chelsea Finn, Karol Hausman, Alexander Herzog, Daniel Ho, Julian Ibarz, Alex Irpan, Eric Jang, Ryan Julian, Dmitry Kalashnikov, Sergey Levine, Yao Lu, Carolina Parada, Kanishka Rao, Pierre Sermanet, Alexander Toshev, Vincent Vanhoucke, and 26 others. 2022 · 2022
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Open-world object manipulation using pre-trained vision-language models
Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Brianna Zitkovich, Fei Xia, Chelsea Finn, and Karol Hausman. 2023 · 2023
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Yanchao Sun, Shuang Ma, Ratnesh Madaan, Rogerio Bonatti, Furong Huang, and Ashish Kapoor. 2023 · 2023
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Chatgpt for robotics: Design principles and model abilities
Sai Vemprala, Rogerio Bonatti, Arthur Bucker, and Ashish Kapoor. 2023 · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
Tony Z. Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn. 2023 · 2023
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Yunfan Jiang, Agrim Gupta, Zichen Zhang, Guanzhi Wang, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, and Linxi Fan. 2022 · 2022
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Masked autoencoding for scalable and generalizable decision making
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CALVIN: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks
Oier Mees, Lukás Hermann, Erick Rosete-Beas, and Wolfram Burgard. 2022 · 2022
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Iso-dream: Isolating and leveraging noncontrollable visual dynamics in world models
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A generalist agent
Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, and Nando de Freitas. 2022 · 2022
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Openflamingo: An open-source framework for training large autoregressive vision-language models
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Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, and 16 others. 2024 · 2024
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π \pi 0 {}_{\mbox{0}} : A vision-language-action flow model for general robot control
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GR-2: A generative video-language-action model with web-scale knowledge for robot manipulation
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Mastering robot manipulation with multimodal prompts through pretraining and multi-task fine-tuning
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Open x-embodiment: Robotic learning datasets and RT-X models : Open x-embodiment collaboration
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Unleashing large-scale video generative pre-training for visual robot manipulation
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A survey on robotics with foundation models: toward embodied AI
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