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Implicit policies parameterized by generative models, such as Diffusion Policy, have become the standard for policy learning and Vision-Language-Action (VLA) models in robotics.
A method for solving the convex programming problem with convergence rate o(1/k2̂)
Yurii Nesterov · 1983
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A tutorial on energy-based learning
Yann LeCun, Sumit Chopra, Raia Hadsell, Aurelio Ranzato, and Fu Jie Huang · 2006
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Efficient reductions for imitation learning
Stéphane Ross and Drew Bagnell · 2010
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Thinking, Fast and Slow
Daniel Kahneman · 2011
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Bayesian learning via stochastic gradient langevin dynamics
Max Welling and Yee Whye Teh · 2011
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On the difficulty of training recurrent neural networks, 2013
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio · 2013
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Deep residual learning for image recognition, 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Sgdr: Stochastic gradient descent with warm restarts, 2017
Ilya Loshchilov and Frank Hutter · 2017
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Root mean square layer normalization, 2019
Biao Zhang and Rico Sennrich · 2019
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Implicit generation and generalization in energy-based models, 2020
Yilun Du and Igor Mordatch · 2020
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Improved contrastive divergence training of energy based models
Yilun Du, Shuang Li, Joshua Tenenbaum, and Igor Mordatch · 2020
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Denoising diffusion probabilistic models, 2020
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Why gradient clipping accelerates training: A theoretical justification for adaptivity, 2020
Jingzhao Zhang, Tianxing He, Suvrit Sra, and Ali Jadbabaie · 2020
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Implicit behavioral cloning, 2021
Pete Florence, Corey Lynch, Andy Zeng, Oscar Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, and Jonathan Tompson · 2021
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Energy-based imitation learning, 2021
Minghuan Liu, Tairan He, Minkai Xu, and Weinan Zhang · 2021
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What matters in learning from offline human demonstrations for robot manipulation, 2021
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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Learning iterative reasoning through energy minimization, 2022
Yilun Du, Shuang Li, Joshua B. Tenenbaum, and Igor Mordatch · 2022
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A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27
Yann LeCun · 2022
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Denoising diffusion implicit models, 2022
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2022
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Hydra: Hybrid robot actions for imitation learning
Suneel Belkhale, Yuchen Cui, and Dorsa Sadigh · 2023
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Get back here: Robust imitation by return-to-distribution planning
Geoffrey Cideron, Baruch Tabanpour, Sebastian Curi, Sertan Girgin, Leonard Hussenot, Gabriel Dulac-Arnold, Matthieu Geist, Olivier Pietquin, and Robert Dadashi · 2023
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Foundation models in robotics: Applications, challenges, and the future, 2023
Roya Firoozi, Johnathan Tucker, Stephen Tian, Anirudha Majumdar, Jiankai Sun, Weiyu Liu, Yuke Zhu, Shuran Song, Ashish Kapoor, Karol Hausman, Brian Ichter, Danny Driess, Jiajun Wu, Cewu Lu, and Mac Schwager · 2023
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On error propagation of diffusion models, 2024
Yangming Li and Mihaela van der Schaar · 2024
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Visual whole-body control for legged loco-manipulation
Minghuan Liu, Zixuan Chen, Xuxin Cheng, Yandong Ji, Ri-Zhao Qiu, Ruihan Yang, and Xiaolong Wang · 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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Equivariant diffusion policy, 2024
Dian Wang, Stephen Hart, David Surovik, Tarik Kelestemur, Haojie Huang, Haibo Zhao, Mark Yeatman, Jiuguang Wang, Robin Walters, and Robert Platt · 2024
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Flowpolicy: Enabling fast and robust 3d flow-based policy via consistency flow matching for robot manipulation, 2024
Qinglun Zhang, Zhen Liu, Haoqiang Fan, Guanghui Liu, Bing Zeng, and Shuaicheng Liu · 2024
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Flow matching for generative modeling, 2023
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2023
Cited alongside, same era.
Input perturbation reduces exposure bias in diffusion models, 2023
Mang Ning, Enver Sangineto, Angelo Porrello, Simone Calderara, and Rita Cucchiara · 2023
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Exploring the limits of transfer learning with a unified text-to-text transformer, 2023
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2023
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Chain-of-thought prompting elicits reasoning in large language models, 2023
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou · 2023
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The generative ai paradox: ”what it can create, it may not understand”, 2023
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, and Yejin Choi · 2023
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π 0 \pi_{0} : A vision-language-action flow model for general robot control, 2024
Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, Liyiming Ke, Sergey Levine, Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Lucy Xiaoyang Shi, James Tanner, Quan Vuong, Anna Walling, Haohuan Wang, and Ury Zhilinsky · 2024
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Spatially visual perception for end-to-end robotic learning, 2024
Travis Davies, Jiahuan Yan, Xiang Chen, Yu Tian, Yueting Zhuang, Yiqi Huang, and Luhui Hu · 2024
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Tenma: Robust cross-embodiment robot manipulation with diffusion transformer, 2025
Travis Davies, Yiqi Huang, Yunxin Liu, Xiang Chen, Huxian Liu, and Luhui Hu · 2025
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Alexi Gladstone, Ganesh Nanduru, Md Mofijul Islam, Peixuan Han, Hyeonjeong Ha, Aman Chadha, Yilun Du, Heng Ji, Jundong Li, and Tariq Iqbal · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al · 2025
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Robograsp: A universal grasping policy for robust robotic control, 2025
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Rdt-1b: a diffusion foundation model for bimanual manipulation, 2025
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Gr00t n1: An open foundation model for generalist humanoid robots, 2025
NVIDIA, :, Johan Bjorck, Fernando Castañeda, Nikita Cherniadev, Xingye Da, Runyu Ding, Linxi ”Jim” Fan, Yu Fang, Dieter Fox, Fengyuan Hu, Spencer Huang, Joel Jang, Zhenyu Jiang, Jan Kautz, Kaushil Kundalia, Lawrence Lao, Zhiqi Li, Zongyu Lin, Kevin Lin, Guilin Liu, Edith Llontop, Loic Magne, Ajay Mandlekar, Avnish Narayan, Soroush Nasiriany, Scott Reed, You Liang Tan, Guanzhi Wang, Zu Wang, Jing Wang, Qi Wang, Jiannan Xiang, Yuqi Xie, Yinzhen Xu, Zhenjia Xu, Seonghyeon Ye, Zhiding Yu, Ao Zhang, Hao Zhang, Yizhou Zhao, Ruijie Zheng, and Yuke Zhu · 2025
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Fast: Efficient action tokenization for vision-language-action models, 2025
Karl Pertsch, Kyle Stachowicz, Brian Ichter, Danny Driess, Suraj Nair, Quan Vuong, Oier Mees, Chelsea Finn, and Sergey Levine · 2025
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Dinov3, 2025
Oriane Siméoni, Huy V. Vo, Maximilian Seitzer, Federico Baldassarre, Maxime Oquab, Cijo Jose, Vasil Khalidov, Marc Szafraniec, Seungeun Yi, Michaël Ramamonjisoa, Francisco Massa, Daniel Haziza, Luca Wehrstedt, Jianyuan Wang, Timothée Darcet, Théo Moutakanni, Leonel Sentana, Claire Roberts, Andrea Vedaldi, Jamie Tolan, John Brandt, Camille Couprie, Julien Mairal, Hervé Jégou, Patrick Labatut, and Piotr Bojanowski · 2025
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Equilibrium matching: Generative modeling with implicit energy-based models, 2025
Runqian Wang and Yilun Du · 2025
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Fp3: A 3d foundation policy for robotic manipulation, 2025
Rujia Yang, Geng Chen, Chuan Wen, and Yang Gao · 2025
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Opendrivevla: Towards end-to-end autonomous driving with large vision language action model, 2025
Xingcheng Zhou, Xuyuan Han, Feng Yang, Yunpu Ma, and Alois C. Knoll · 2025
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Unified world models: Coupling video and action diffusion for pretraining on large robotic datasets, 2025
Chuning Zhu, Raymond Yu, Siyuan Feng, Benjamin Burchfiel, Paarth Shah, and Abhishek Gupta · 2025
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