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By transferring knowledge from large, diverse, task-agnostic datasets, modern machine learning models can solve specific downstream tasks either zero-shot or with small task-specific datasets to a high level of performance.
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Matt MacMahon, Brian Stankiewicz, and Benjamin Kuipers · 2006
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Robotic grasping of novel objects
Ashutosh Saxena, Justin Driemeyer, Justin Kearns, and Andrew Ng · 2006
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Toward understanding natural language directions
Thomas Kollar, Stefanie Tellex, Deb Roy, and Nicholas Roy · 2010
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Doubly robust policy evaluation and learning
Miroslav Dudík, John Langford, and Lihong Li · 2011
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RetinaGAN: An object-aware approach to sim-to-real transfer, 2020
Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, and Yunfei Bai · 2011
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Understanding natural language commands for robotic navigation and mobile manipulation
Stefanie Tellex, Thomas Kollar, Steven Dickerson, Matthew Walter, Ashis Banerjee, Seth Teller, and Nicholas Roy · 2011
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Multi-task policy search for robotics
Marc Peter Deisenroth, Peter Englert, Jan Peters, and Dieter Fox · 2014
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A bayesian developmental approach to robotic goal-based imitation learning
Michael Jae-Yoon Chung, Abram L Friesen, Dieter Fox, Andrew N Meltzoff, and Rajesh PN Rao · 2015
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Deep learning for detecting robotic grasps
Ian Lenz, Honglak Lee, and Ashutosh Saxena · 2015
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Listen, attend, and walk: Neural mapping of navigational instructions to action sequences
Hongyuan Mei, Mohit Bansal, and Matthew R Walter · 2016
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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
Lerrel Pinto and Abhinav Gupta · 2016
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Learning modular neural network policies for multi-task and multi-robot transfer
Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, and Sergey Levine · 2017
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Bootstrapping with models: Confidence intervals for off-policy evaluation
Josiah P Hanna, Peter Stone, and Scott Niekum · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Learning a visuomotor controller for real world robotic grasping using simulated depth images
Ulrich Viereck, Andreas Pas, Kate Saenko, and Robert Platt · 2017
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Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, et al · 2018
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Robot learning in homes: Improving generalization and reducing dataset bias
Abhinav Gupta, Adithyavairavan Murali, Dhiraj Prakashchand Gandhi, and Lerrel Pinto · 2018
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Scalable deep reinforcement learning for vision-based robotic manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, et al · 2018
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Image transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, and Aaron Courville · 2018
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Multiple interactions made easy (mime): Large scale demonstrations data for imitation
Pratyusha Sharma, Lekha Mohan, Lerrel Pinto, and Abhinav Gupta · 2018
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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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Robonet: Large-scale multi-robot learning
Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, and Chelsea Finn · 2019
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Scene memory transformer for embodied agents in long-horizon tasks
Decision transformer: Reinforcement learning via sequence modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch · 2021
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Bridge data: Boosting generalization of robotic skills with cross-domain datasets
Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, and Sergey Levine · 2021
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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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Reinforcement learning as one big sequence modeling problem
Michael Janner, Qiyang Li, and Sergey Levine · 2021
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Episodic transformer for vision-and-language navigation
Alexander Pashevich, Cordelia Schmid, and Chen Sun · 2021
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Kuan Fang, Alexander Toshev, Li Fei-Fei, and Silvio Savarese · 2019
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Multi-task hierarchical imitation learning for home automation
Roy Fox, Ron Berenstein, Ion Stoica, and Ken Goldberg · 2019
Cited alongside, same era.
Off-policy evaluation via off-policy classification
Alexander Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, and Sergey Levine · 2019
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Antonin Raffin, Ashley Hill, René Traoré, Timothée Lesort, Natalia Díaz-Rodríguez, and David Filliat · 2019
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EfficientNet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc Le · 2019
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Motion reasoning for goal-based imitation learning
De-An Huang, Yu-Wei Chao, Chris Paxton, Xinke Deng, Li Fei-Fei, Juan Carlos Niebles, Animesh Garg, and Dieter Fox · 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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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, et al · 2021
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Tokenlearner: Adaptive space-time tokenization for videos
Michael Ryoo, AJ Piergiovanni, Anurag Arnab, Mostafa Dehghani, and Anelia Angelova · 2021
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Cliport: What and where pathways for robotic manipulation
Mohit Shridhar, Lucas Manuelli, and Dieter Fox · 2021
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Lancon-learn: Learning with language to enable generalization in multi-task manipulation
Andrew Silva, Nina Moorman, William Silva, Zulfiqar Zaidi, Nakul Gopalan, and Matthew Gombolay · 2021
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Hierarchical task learning from language instructions with unified transformers and self-monitoring
Yichi Zhang and Joyce Chai · 2021
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Do as I can, not as I say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, et al · 2022
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Metamorph: Learning universal controllers with transformers
Agrim Gupta, Linxi Fan, Surya Ganguli, and Li Fei-Fei · 2022
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Vima: General robot manipulation with multimodal prompts
Yunfan Jiang, Agrim Gupta, Zichen Zhang, Guanzhi Wang, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, and Linxi Fan · 2022
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Learning language-conditioned robot behavior from offline data and crowd-sourced annotation
Suraj Nair, Eric Mitchell, Kevin Chen, Silvio Savarese, Chelsea Finn, et al · 2022
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Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, et al · 2022
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Behavior transformers: Cloning k k modes with one stone
Nur Muhammad Mahi Shafiullah, Zichen Jeff Cui, Ariuntuya Altanzaya, and Lerrel Pinto · 2022
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Perceiver-actor: A multi-task transformer for robotic manipulation
Mohit Shridhar, Lucas Manuelli, and Dieter Fox · 2022
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