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Deploying large, complex policies in the real world requires the ability to steer them to fit the needs of a situation.
Dream to control: Learning behaviors by latent imagination
Danijar Hafner, Timothy Lillicrap, Jimmy Ba, and Mohammad Norouzi · 1912
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ALOHA unleashed: A simple recipe for robot dexterity
Tony Z. Zhao, Jonathan Tompson, Danny Driess, Pete Florence, Seyed Kamyar Seyed Ghasemipour, Chelsea Finn, and Ayzaan Wahid · 1924
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A generalized iterative LQG method for locally-optimal feedback control of constrained nonlinear stochastic systems
E. Todorov and Weiwei Li · 2005
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Mastering atari with discrete world models, b
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, and Jimmy Ba · 2010
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
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Hindsight experience replay
Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, OpenAI Pieter Abbeel, and Wojciech Zaremba · 2017
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Deep visual foresight for planning robot motion
Chelsea Finn and Sergey Levine · 2017
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Learning latent dynamics for planning from pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, and James Davidson · 2018
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Zero-shot visual imitation
Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, and Trevor Darrell · 2018
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Goal-conditioned imitation learning
Yiming Ding, Carlos Florensa, Pieter Abbeel, and Mariano Phielipp · 2019
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Stochastic latent actor-critic: Deep reinforcement learning with a latent variable model
Alex X. Lee, Anusha Nagabandi, Pieter Abbeel, and Sergey Levine · 2020
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Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Temporal difference learning for model predictive control
Nicklas Hansen, Xiaolong Wang, and Hao Su · 2022
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Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
Cited alongside, same era.
Daydreamer: World models for physical robot learning
Philipp Wu, Alejandro Escontrela, Danijar Hafner, Ken Goldberg, and Pieter Abbeel · 2022
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Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
Td-mpc2: Scalable, robust world models for continuous control, 2024
Nicklas Hansen, Hao Su, and Xiaolong Wang · 2024
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Data scaling laws in imitation learning for robotic manipulation
Fanqi Lin, Yingdong Hu, Pingyue Sheng, Chuan Wen, Jiacheng You, and Yang Gao · 2024
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Multi-task interactive robot fleet learning with visual world models
Huihan Liu, Yu Zhang, Vaarij Betala, Evan Zhang, James Liu, Crystal Ding, and Yuke Zhu · 2024
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Steering your generalists: Improving robotic foundation models via value guidance
Mitsuhiko Nakamoto, Oier Mees, Aviral Kumar, and Sergey Levine · 2024
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Yell at your robot: Improving on-the-fly from language corrections
Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, and Chelsea Finn · 2024
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Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin CM Burchfiel, and Shuran Song · 2023
Cited alongside, same era.
No, to the right: Online language corrections for robotic manipulation via shared autonomy
Yuchen Cui, Siddharth Karamcheti, Raj Palleti, Nidhya Shivakumar, Percy Liang, and Dorsa Sadigh · 2023
Cited alongside, same era.
Transformers are sample-efficient world models
Vincent Micheli, Eloi Alonso, and François Fleuret · 2023
Cited alongside, same era.
Goal conditioned imitation learning using score-based diffusion policies
Moritz Reuss, Maximilian Li, Xiaogang Jia, and Rudolf Lioutikov · 2023
Cited alongside, same era.
Transformer-based world models are happy with 100k interactions
Jan Robine, Marc Höftmann, Tobias Uelwer, and Stefan Harmeling · 2023
Cited alongside, same era.
Universal manipulation interface: In-the-wild robot teaching without in-the-wild robots
Cheng Chi, Zhenjia Xu, Chuer Pan, Eric Cousineau, Benjamin Burchfiel, Siyuan Feng, Russ Tedrake, and Shuran Song · 2024
Cited alongside, same era.
Is conditional generative modeling all you need for decision-making?
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua Tenenbaum, Tommi Jaakkola, and Pulkit Agrawal
Cited in the paper.
Yuejiang Liu, Jubayer Ibn Hamid, Annie Xie, Yoonho Lee, Maximilian Du, and Chelsea Finn · 2025
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Generalizing safety beyond collision-avoidance via latent-space reachability analysis
Kensuke Nakamura, Lasse Peters, and Andrea Bajcsy · 2025
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Lumos: Language-conditioned imitation learning with world models
Iman Nematollahi, Branton DeMoss, Akshay L Chandra, Nick Hawes, Wolfram Burgard, and Ingmar Posner · 2025
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Steering your diffusion policy with latent space reinforcement learning, 2025
Andrew Wagenmaker, Mitsuhiko Nakamoto, Yunchu Zhang, Seohong Park, Waleed Yagoub, Anusha Nagabandi, Abhishek Gupta, and Sergey Levine · 2025
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From foresight to forethought: Vlm-in-the-loop policy steering via latent alignment, 2025
Yilin Wu, Ran Tian, Gokul Swamy, and Andrea Bajcsy · 2025
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