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Grounding the common-sense reasoning of Large Language Models (LLMs) in physical domains remains a pivotal yet unsolved problem for embodied AI.
Explanation-based manipulator learning: Acquisition of planning ability through observation
Alberto Segre and Gerald DeJong · 1985
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Explanation-based learning: An alternative view
Gerald DeJong and Raymond Mooney · 1986
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Rapidly-Exploring Random Trees: A New Tool for Path Planning
Steven LaValle · 1998
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Mechanics of robotic manipulation
Matthew T Mason · 2001
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Multi-modal motion planning in non-expansive spaces
Kris Hauser and Jean-Claude Latombe · 2010
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A reduction of imitation learning and structured prediction to no-regret online learning
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Understanding Natural Language Commands for Robotic Navigation and Mobile Manipulation
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Alignment-Based Compositional Semantics for Instruction Following
Jacob Andreas and Dan Klein · 2015
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Modular Multitask Reinforcement Learning with Policy Sketches
Jacob Andreas, Dan Klein, and Sergey Levine · 2017
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Teaching multiple tasks to an rl agent using ltl
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, and Sheila A. McIlraith · 2018
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Counterfactuals in explainable artificial intelligence (xai): Evidence from human reasoning
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Language as an Abstraction for Hierarchical Deep Reinforcement Learning
Yiding Jiang, Shixiang Shane Gu, Kevin P Murphy, and Chelsea Finn · 2019
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A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf, and Isabel Valera · 2020
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Language conditioned imitation learning over unstructured data
Corey Lynch and Pierre Sermanet · 2020
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Program guided agent
Shao-Hua Sun, Te-Lin Wu, and Joseph J Lim · 2020
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robosuite: A modular simulation framework and benchmark for robot learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar, Roberto Martín-Martín, Abhishek Joshi, Soroush Nasiriany, and Yifeng Zhu · 2020
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Learning and planning for temporally extended tasks in unknown environments, 2021
Christopher Bradley, Adam Pacheck, Gregory J. Stein, Sebastian Castro, Hadas Kress-Gazit, and Nicholas Roy · 2021
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Modular Networks for Compositional Instruction Following
Rodolfo Corona, Daniel Fried, Coline Devin, Dan Klein, and Trevor Darrell · 2021
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Voxposer: Composable 3d value maps for robotic manipulation with language models
Wenlong Huang, Chen Wang, Ruohan Zhang, Yunzhu Li, Jiajun Wu, and Li Fei-Fei · 2023
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Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Text2motion: From natural language instructions to feasible plans
Kevin Lin, Christopher Agia, Toki Migimatsu, Marco Pavone, and Jeannette Bohg · 2023
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LLM+ P: Empowering Large Language Models with Optimal Planning Proficiency
Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, and Peter Stone · 2023
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Learning Rational Subgoals from Demonstrations and Instructions
Zhezheng Luo, Jiayuan Mao, Jiajun Wu, Tomás Lozano-Pérez, Joshua B Tenenbaum, and Leslie Pack Kaelbling · 2023
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Instance-based counterfactual explanations for time series classification
Eoin Delaney, Derek Greene, and Mark T Keane · 2021
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Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 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, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, et al · 2022
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Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
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Pre-trained language models for interactive decision-making
Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, et al · 2022
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Skill Induction and Planning with Latent Language
Pratyusha Sharma, Antonio Torralba, and Jacob Andreas · 2022
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Interactive language: Talking to robots in real time
Corey Lynch, Ayzaan Wahid, Jonathan Tompson, Tianli Ding, James Betker, Robert Baruch, Travis Armstrong, and Pete Florence · 2023
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Underactuated Robotics
Russ Tedrake · 2023
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Voyager: An Open-Ended Embodied Agent with Large Language Models
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, and Anima Anandkumar · 2023
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Gello: A general, low-cost, and intuitive teleoperation framework for robot manipulators
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Learning fine-grained bimanual manipulation with low-cost hardware
Tony Z Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn · 2023
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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
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Mobile aloha: Learning bimanual mobile manipulation with low-cost whole-body teleoperation
Zipeng Fu, Tony Z Zhao, and Chelsea Finn · 2024
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