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Imitation learning has emerged as a promising approach towards building generalist robots.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Efficient reductions for imitation learning
Stephane Ross and Drew Bagnell · 2010
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Deep residual learning for image recognition
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2015
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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The” something something” video database for learning and evaluating visual common sense
Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fruend, Peter Yianilos, Moritz Mueller-Freitag, et al · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Denoising diffusion probabilistic models, 2020
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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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
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What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Learning by watching: Physical imitation of manipulation skills from human videos, 2021
Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, and Animesh Garg · 2021
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katie Millicah, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karen Simonyan · 2022
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Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models
Fan Bao, Chongxuan Li, Jun Zhu, and Bo Zhang · 2022
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Unimask: Unified inference in sequential decision problems, 2022
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, and Sam Devlin · 2022
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Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2022
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Behavior transformers: Cloning k k modes with one stone, 2022
Nur Muhammad Mahi Shafiullah, Zichen Jeff Cui, Ariuntuya Altanzaya, and Lerrel Pinto · 2022
Cited alongside, same era.
Affordances from human videos as a versatile representation for robotics, 2023
Shikhar Bahl, Russell Mendonca, Lili Chen, Unnat Jain, and Deepak Pathak · 2023
Cited alongside, same era.
One transformer fits all distributions in multi-modal diffusion at scale, 2023
Diffusion forcing: Next-token prediction meets full-sequence diffusion, 2024
Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, and Vincent Sitzmann · 2024
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Open x-embodiment: Robotic learning datasets and rt-x models, 2024
Embodiment Collaboration · 2024
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Vision transformers need registers
Timothée Darcet, Maxime Oquab, Julien Mairal, and Piotr Bojanowski · 2024
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The ingredients for robotic diffusion transformers
Sudeep Dasari, Oier Mees, Sebastian Zhao, Mohan Kumar Srirama, and Sergey Levine · 2024
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Video prediction policy: A generalist robot policy with predictive visual representations, 2024
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Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, and Jun Zhu · 2023
Cited alongside, same era.
Stable video diffusion: Scaling latent video diffusion models to large datasets, 2023
Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, Varun Jampani, and Robin Rombach · 2023
Cited alongside, same era.
Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, and Shuran Song · 2023
Cited alongside, same era.
From play to policy: Conditional behavior generation from uncurated robot data
Zichen Jeff Cui, Yibin Wang, Nur Muhammad Mahi Shafiullah, and Lerrel Pinto · 2023
Cited alongside, same era.
Flow matching for generative modeling
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2023
Cited alongside, same era.
LIBERO: Benchmarking knowledge transfer for lifelong robot learning
Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, qiang liu, Yuke Zhu, and Peter Stone · 2023
Cited alongside, same era.
Mimicplay: Long-horizon imitation learning by watching human play, 2023
Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, and Anima Anandkumar · 2023
Cited alongside, same era.
Unleashing large-scale video generative pre-training for visual robot manipulation, 2023
Hongtao Wu, Ya Jing, Chilam Cheang, Guangzeng Chen, Jiafeng Xu, Xinghang Li, Minghuan Liu, Hang Li, and Tao Kong · 2023
Cited alongside, same era.
Yucheng Hu, Yanjiang Guo, Pengchao Wang, Xiaoyu Chen, Yen-Jen Wang, Jianke Zhang, Koushil Sreenath, Chaochao Lu, and Jianyu Chen · 2024
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Openvla: An open-source vision-language-action model
Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Foster, Grace Lam, Pannag Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, and Chelsea Finn · 2024
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Behavior generation with latent actions, 2024
Seungjae Lee, Yibin Wang, Haritheja Etukuru, H. Jin Kim, Nur Muhammad Mahi Shafiullah, and Lerrel Pinto · 2024
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Ssm meets video diffusion models: Efficient long-term video generation with structured state spaces
Yuta Oshima, Shohei Taniguchi, Masahiro Suzuki, and Yutaka Matsuo · 2024
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SDXL: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2024
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Octo: An open-source generalist robot policy, 2024
Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Pannag Sanketi, Quan Vuong, Ted Xiao, Dorsa Sadigh, Chelsea Finn, and Sergey Levine · 2024
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Latent action pretraining from videos, 2024
Seonghyeon Ye, Joel Jang, Byeongguk Jeon, Sejune Joo, Jianwei Yang, Baolin Peng, Ajay Mandlekar, Reuben Tan, Yu-Wei Chao, Bill Yuchen Lin, Lars Liden, Kimin Lee, Jianfeng Gao, Luke Zettlemoyer, Dieter Fox, and Minjoon Seo · 2024
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Aloha unleashed: A simple recipe for robot dexterity, 2024
Tony Z. Zhao, Jonathan Tompson, Danny Driess, Pete Florence, Kamyar Ghasemipour, Chelsea Finn, and Ayzaan Wahid · 2024
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Transfusion: Predict the next token and diffuse images with one multi-modal model, 2024
Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Xuezhe Ma, Luke Zettlemoyer, and Omer Levy · 2024
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Cosmos world foundation model platform for physical ai
NVIDIA Research · 2025
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