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Recent advancements in Artificial Intelligence (AI) have largely been propelled by scaling.
Alvinn: An autonomous land vehicle in a neural network
Dean A Pomerleau · 1989
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Human-in-the-loop imitation learning using remote teleoperation, 2020b
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Sergey Levine, Peter Pastor, Alex Krizhevsky, and Deirdre Quillen · 2016
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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
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Attention is all you need
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Qt-opt: Scalable deep reinforcement learning for vision-based robotic manipulation
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Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Xi Chen, Ken Goldberg, and Pieter Abbeel · 2018
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Reinforcement and imitation learning for diverse visuomotor skills
Yuke Zhu, Ziyu Wang, Josh Merel, Andrei Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, et al · 2018
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Robonet: Large-scale multi-robot learning
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Ajay Mandlekar, Jonathan Booher, Max Spero, Albert Tung, Anchit Gupta, Yuke Zhu, Animesh Garg, Silvio Savarese, and Li Fei-Fei · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Rlbench: The robot learning benchmark & learning environment
Stephen James, Zicong Ma, David Rovick Arrojo, and Andrew J Davison · 2020
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Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu · 2020
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Transporter networks: Rearranging the visual world for robotic manipulation
Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, and Johnny Lee · 2020
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Yuke Zhu, Josiah Wong, Ajay Mandlekar, and Roberto Martín-Martín · 2020
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Bc-z: Zero-shot task generalization with robotic imitation learning
Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, and Chelsea Finn · 2021
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Mt-opt: Continuous multi-task robotic reinforcement learning at scale
Dmitry Kalashnikov, Jacob Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, and Karol Hausman · 2021
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A workflow for offline model-free robotic reinforcement learning
MuJoCo Menagerie: A collection of high-quality simulation models for MuJoCo, 2022
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Q-transformer: Scalable offline reinforcement learning via autoregressive q-functions
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Open X-Embodiment: Robotic learning datasets and RT-X models
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Imitating task and motion planning with visuomotor transformers
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igibson 2.0: Object-centric simulation for robot learning of everyday household tasks
Chengshu Li, Fei Xia, Roberto Martín-Martín, Michael Lingelbach, Sanjana Srivastava, Bokui Shen, Kent Vainio, Cem Gokmen, Gokul Dharan, Tanish Jain, et al · 2021
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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
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Libero: Benchmarking knowledge transfer for lifelong robot learning
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Mimicgen: A data generation system for scalable robot learning using human demonstrations
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Large language models as generalizable policies for embodied tasks
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Droid: A large-scale in-the-wild robot manipulation dataset, 2024
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