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Dorsa Sadigh

On the Opportunities and Risks of Foundation Models


Aug 18, 2021
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

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* Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) 
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APReL: A Library for Active Preference-based Reward Learning Algorithms


Aug 16, 2021
Erdem Bıyı k, Aditi Talati, Dorsa Sadigh

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* 5 pages, 1 figures. Library is available at: https://github.com/Stanford-ILIAD/APReL 
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Social Coordination and Altruism in Autonomous Driving


Jul 20, 2021
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah

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* This paper is submitted to IEEE Transactions on Intelligent Vehicles on June 2021 
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Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic


Jul 12, 2021
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah

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* Accepted to 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021) - Workshop on Autonomous Driving: Perception, Prediction and Planning 
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Learning Latent Actions to Control Assistive Robots


Jul 10, 2021
Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh

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Social Coordination through Altruism in Autonomous Driving


Jul 06, 2021
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah

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* This paper is submitted to IEEE Transactions on Intelligent Transportation Systems on June 2021 
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Cooperative Autonomous Vehicles that Sympathize with Human Drivers


Jul 02, 2021
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah

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* Accepted in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 
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Targeted Data Acquisition for Evolving Negotiation Agents


Jun 16, 2021
Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh

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* The Thirty-eighth International Conference on Machine Learning 
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Emergent Prosociality in Multi-Agent Games Through Gifting


May 13, 2021
Woodrow Z. Wang, Mark Beliaev, Erdem Bıyık, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh

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* 9 pages, 6 figures, IJCAI 2021 
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Learning Visually Guided Latent Actions for Assistive Teleoperation


May 02, 2021
Siddharth Karamcheti, Albert J. Zhai, Dylan P. Losey, Dorsa Sadigh

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* Accepted at Learning for Dynamics and Control (L4DC) 2021. 12 pages, 4 figures 
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On the Critical Role of Conventions in Adaptive Human-AI Collaboration


Apr 07, 2021
Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh

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* 9th International Conference on Learning Representations (ICLR 2021) 
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Learning Human Objectives from Sequences of Physical Corrections


Mar 31, 2021
Mengxi Li, Alper Canberk, Dylan P. Losey, Dorsa Sadigh

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* 7 pages, 4 figures 
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Learning from Imperfect Demonstrations from Agents with Varying Dynamics


Mar 10, 2021
Zhangjie Cao, Dorsa Sadigh

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* Accpeted by ICRA 2021 
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ELLA: Exploration through Learned Language Abstraction


Mar 10, 2021
Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh

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* 13 pages, 8 figures 
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Transfer Reinforcement Learning across Homotopy Classes


Feb 11, 2021
Zhangjie Cao, Minae Kwon, Dorsa Sadigh

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* Accepted by IEEE Robotics and Automation Letters 2021 
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Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic


Dec 28, 2020
Mark Beliaev, Erdem Bıyık, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani

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* To appear at ICCPS 2021. 11 pages, 4 figures 
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Learning Latent Representations to Influence Multi-Agent Interaction


Nov 12, 2020
Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh

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* Conference on Robot Learning (CoRL) 2020. Supplementary website at https://sites.google.com/view/latent-strategies/ 
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ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes


Nov 09, 2020
Kejun Li, Maegan Tucker, Erdem Bıyık, Ellen Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames

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* 6 pages; 7 figures 
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Learning Adaptive Language Interfaces through Decomposition


Oct 11, 2020
Siddharth Karamcheti, Dorsa Sadigh, Percy Liang

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* Accepted at the 1st Workshop for Interactive and Executable Semantic Parsing (IntEx-SemPar) @ EMNLP 2020. 11 pages, 5 figures 
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Multi-Agent Safe Planning with Gaussian Processes


Aug 10, 2020
Zheqing Zhu, Erdem Bıyık, Dorsa Sadigh

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* 9 pages, 5 figures. Published at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020 
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Learning User-Preferred Mappings for Intuitive Robot Control


Jul 22, 2020
Mengxi Li, Dylan P. Losey, Jeannette Bohg, Dorsa Sadigh

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* 8 pages, 7 figures, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020 
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Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving


Jul 01, 2020
Zhangjie Cao, Erdem Bıyık, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh

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* 10 pages, 7 figures. Published at Robotics: Science and Systems (RSS) 2020 
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Formalizing and Guaranteeing* Human-Robot Interaction


Jun 30, 2020
Hadas Kress-Gazit, Kerstin Eder, Guy Hoffman, Henny Admoni, Brenna Argall, Ruediger Ehlers, Christoffer Heckman, Nils Jansen, Ross Knepper, Jan Křetínský, Shelly Levy-Tzedek, Jamy Li, Todd Murphey, Laurel Riek, Dorsa Sadigh

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Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences


Jun 24, 2020
Erdem Bıyık, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh

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* 19 pages, 17 figures. Submitted to The International Journal of Robotics Research (IJRR) 
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Active Preference-Based Gaussian Process Regression for Reward Learning


Jun 03, 2020
Erdem Bıyık, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh

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* Proceedings of Robotics: Science and Systems (RSS), July 2020 
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Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints


May 29, 2020
Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg

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* Robotics Science and Systems (RSS) 2020; Source code at https://github.com/sisl/SCoBA.jl 
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