Dorsa Sadigh

According to our database, Dorsa Sadigh authored at least 154 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Explore until Confident: Efficient Exploration for Embodied Question Answering.

Allen Z. Ren, Jaden Clark, Anushri Dixit, Masha Itkina, Anirudha Majumdar, Dorsa Sadigh

CoRR, 2024

Efficient Data Collection for Robotic Manipulation via Compositional Generalization.

Jensen Gao, Annie Xie, Ted Xiao, Chelsea Finn, Dorsa Sadigh

CoRR, 2024

RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches.

Priya Sundaresan, Quan Vuong, Jiayuan Gu, Peng Xu, Ted Xiao, Sean Kirmani, Tianhe Yu, Michael Stark, Ajinkya Jain, Karol Hausman, Dorsa Sadigh, Jeannette Bohg, Stefan Schaal

CoRR, 2024

RT-H: Action Hierarchies Using Language.

Suneel Belkhale, Tianli Ding, Ted Xiao, Pierre Sermanet, Quon Vuong, Jonathan Tompson, Yevgen Chebotar, Debidatta Dwibedi, Dorsa Sadigh

CoRR, 2024

Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation.

Jonathan Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah, Quan Vuong, Chelsea Finn, Dorsa Sadigh, Sergey Levine

CoRR, 2024

Batch Active Learning of Reward Functions from Human Preferences.

Erdem Biyik, Nima Anari, Dorsa Sadigh

CoRR, 2024

Learning to Learn Faster from Human Feedback with Language Model Predictive Control.

Jacky Liang, Fei Xia, Wenhao Yu, Andy Zeng, Montserrat Gonzalez Arenas, Maria Attarian, Maria Bauzá, Matthew Bennice, Alex Bewley, Adil Dostmohamed, Chuyuan Kelly Fu, Nimrod Gileadi, Marissa Giustina, Keerthana Gopalakrishnan, Leonard Hasenclever, Jan Humplik, Jasmine Hsu, Nikhil J. Joshi, Ben Jyenis, J. Chase Kew, Sean Kirmani, Tsang-Wei Edward Lee, Kuang-Huei Lee, Assaf Hurwitz Michaely, Joss Moore, Ken Oslund, Dushyant Rao, Allen Z. Ren, Baruch Tabanpour, Quan Vuong, Ayzaan Wahid, Ted Xiao, Ying Xu, Vincent Zhuang, Peng Xu, Erik Frey, Ken Caluwaerts, Tingnan Zhang, Brian Ichter, Jonathan Tompson, Leila Takayama, Vincent Vanhoucke, Izhak Shafran, Maja J. Mataric, Dorsa Sadigh, Nicolas Heess, Kanishka Rao, Nik Stewart, Jie Tan, Carolina Parada

CoRR, 2024

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models.

Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, Dorsa Sadigh

CoRR, 2024

AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents.

Michael Ahn, Debidatta Dwibedi, Chelsea Finn, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Karol Hausman, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Sean Kirmani, Isabel Leal, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Sharath Maddineni, Kanishka Rao, Dorsa Sadigh, Pannag Sanketi, Pierre Sermanet, Quan Vuong, Stefan Welker, Fei Xia, Ted Xiao, Peng Xu, Steve Xu, Zhuo Xu

CoRR, 2024

SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities.

Boyuan Chen, Zhuo Xu, Sean Kirmani, Brian Ichter, Danny Driess, Pete Florence, Dorsa Sadigh, Leonidas J. Guibas, Fei Xia

CoRR, 2024

Generative Expressive Robot Behaviors using Large Language Models.

Karthik Mahadevan, Jonathan Chien, Noah Brown, Zhuo Xu, Carolina Parada, Fei Xia, Andy Zeng, Leila Takayama, Dorsa Sadigh

Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024

2023

Robots That Can See: Leveraging Human Pose for Trajectory Prediction.

Tim Salzmann, Hao-Tien Lewis Chiang, Markus Ryll, Dorsa Sadigh, Carolina Parada, Alex Bewley

IEEE Robotics Autom. Lett., November, 2023

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator.

Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter

CoRR, 2023

Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections.

Lihan Zha, Yuchen Cui, Li-Heng Lin, Minae Kwon, Montserrat Gonzalez Arenas, Andy Zeng, Fei Xia, Dorsa Sadigh

CoRR, 2023

Imitation Bootstrapped Reinforcement Learning.

Hengyuan Hu, Suvir Mirchandani, Dorsa Sadigh

CoRR, 2023

Contrastive Preference Learning: Learning from Human Feedback without RL.

Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh

CoRR, 2023

Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

Open X.-Embodiment Collaboration, Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Raj, Anikait Singh, Anthony Brohan, Antonin Raffin, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Brian Ichter, Cewu Lu, Charles Xu, Chelsea Finn, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Chuer Pan, Chuyuan Fu, Coline Devin, Danny Driess, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Federico Ceola, Fei Xia, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Giulio Schiavi, Gregory Kahn, Hao Su, Haoshu Fang, Haochen Shi, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Igor Mordatch, Ilija Radosavovic, et al.

CoRR, 2023

Robots That Can See: Leveraging Human Pose for Trajectory Prediction.

Tim Salzmann, Lewis Chiang, Markus Ryll, Dorsa Sadigh, Carolina Parada, Alex Bewley

CoRR, 2023

Physically Grounded Vision-Language Models for Robotic Manipulation.

Jensen Gao, Bidipta Sarkar, Fei Xia, Ted Xiao, Jiajun Wu, Brian Ichter, Anirudha Majumdar, Dorsa Sadigh

CoRR, 2023

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell

CoRR, 2023

Toward Grounded Social Reasoning.

Minae Kwon, Hengyuan Hu, Vivek Myers, Siddharth Karamcheti, Anca D. Dragan, Dorsa Sadigh

CoRR, 2023

Strategic Reasoning with Language Models.

Kanishk Gandhi, Dorsa Sadigh, Noah D. Goodman

CoRR, 2023

Language-Driven Representation Learning for Robotics.

Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets.

Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

RoboCLIP: One Demonstration is Enough to Learn Robot Policies.

Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Parallel Sampling of Diffusion Models.

Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Diverse Conventions for Human-AI Collaboration.

Bidipta Sarkar, Andy Shih, Dorsa Sadigh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Inverse Preference Learning: Preference-based RL without a Reward Function.

Joey Hejna, Dorsa Sadigh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Data Quality in Imitation Learning.

Suneel Belkhale, Yuchen Cui, Dorsa Sadigh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations.

Yilun Hao, Ruinan Wang, Zhangjie Cao, Zihan Wang, Yuchen Cui, Dorsa Sadigh

IROS, 2023

Soy: An Efficient MILP Solver for Piecewise-Affine Systems.

Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett

IROS, 2023

In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing.

Lorenzo Shaikewitz, Yilin Wu, Suneel Belkhale, Jennifer Grannen, Priya Sundaresan, Dorsa Sadigh

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Active Reward Learning from Online Preferences.

Vivek Myers, Erdem Biyik, Dorsa Sadigh

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation.

Mengxi Li, Rika Antonova, Dorsa Sadigh, Jeannette Bohg

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Generating Language Corrections for Teaching Physical Control Tasks.

Megha Srivastava, Noah D. Goodman, Dorsa Sadigh

Proceedings of the International Conference on Machine Learning, 2023

Long Horizon Temperature Scaling.

Andy Shih, Dorsa Sadigh, Stefano Ermon

Proceedings of the International Conference on Machine Learning, 2023

Language Instructed Reinforcement Learning for Human-AI Coordination.

Hengyuan Hu, Dorsa Sadigh

Proceedings of the International Conference on Machine Learning, 2023

Distance Weighted Supervised Learning for Offline Interaction Data.

Joey Hejna, Jensen Gao, Dorsa Sadigh

Proceedings of the International Conference on Machine Learning, 2023

Reward Design with Language Models.

Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

No, to the Right: Online Language Corrections for Robotic Manipulation via Shared Autonomy.

Yuchen Cui, Siddharth Karamcheti, Raj Palleti, Nidhya Shivakumar, Percy Liang, Dorsa Sadigh

Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, 2023

Polybot: Training One Policy Across Robots While Embracing Variability.

Jonathan Heewon Yang, Dorsa Sadigh, Chelsea Finn

Proceedings of the Conference on Robot Learning, 2023

KITE: Keypoint-Conditioned Policies for Semantic Manipulation.

Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh, Jeannette Bohg

Proceedings of the Conference on Robot Learning, 2023

Learning Sequential Acquisition Policies for Robot-Assisted Feeding.

Priya Sundaresan, Jiajun Wu, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2023

Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners.

Allen Z. Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu, Dorsa Sadigh, Andy Zeng, Anirudha Majumdar

Proceedings of the Conference on Robot Learning, 2023

Large Language Models as General Pattern Machines.

Suvir Mirchandani, Fei Xia, Pete Florence, Brian Ichter, Danny Driess, Montserrat Gonzalez Arenas, Kanishka Rao, Dorsa Sadigh, Andy Zeng

Proceedings of the Conference on Robot Learning, 2023

Gesture-Informed Robot Assistance via Foundation Models.

Li-Heng Lin, Yuchen Cui, Yilun Hao, Fei Xia, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2023

Stabilize to Act: Learning to Coordinate for Bimanual Manipulation.

Jennifer Grannen, Yilin Wu, Brandon Vu, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2023

HYDRA: Hybrid Robot Actions for Imitation Learning.

Suneel Belkhale, Yuchen Cui, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2023

Language to Rewards for Robotic Skill Synthesis.

Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montserrat Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, Brian Ichter, Ted Xiao, Peng Xu, Andy Zeng, Tingnan Zhang, Nicolas Heess, Dorsa Sadigh, Jie Tan, Yuval Tassa, Fei Xia

Proceedings of the Conference on Robot Learning, 2023

Interactive Learning and Control in the Era of Large Models.

Dorsa Sadigh

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Social Coordination and Altruism in Autonomous Driving.

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

IEEE Trans. Intell. Transp. Syst., 2022

Learning reward functions from diverse sources of human feedback: Optimally integrating demonstrations and preferences.

Erdem Biyik, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh

Int. J. Robotics Res., 2022

How do people incorporate advice from artificial agents when making physical judgments?

Erik Brockbank, Haoliang Wang, Justin Yang, Suvir Mirchandani, Erdem Biyik, Dorsa Sadigh, Judith E. Fan

CoRR, 2022

Toward verified artificial intelligence.

Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry

Commun. ACM, 2022

Learning latent actions to control assistive robots.

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

Auton. Robots, 2022

Dynamic multi-robot task allocation under uncertainty and temporal constraints.

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

Auton. Robots, 2022

Assistive Teaching of Motor Control Tasks to Humans.

Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Training and Inference on Any-Order Autoregressive Models the Right Way.

Andy Shih, Dorsa Sadigh, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Weakly Supervised Correspondence Learning.

Zihan Wang, Zhangjie Cao, Yilun Hao, Dorsa Sadigh

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Learning from Imperfect Demonstrations via Adversarial Confidence Transfer.

Zhangjie Cao, Zihan Wang, Dorsa Sadigh

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction.

Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Balancing Efficiency and Comfort in Robot-Assisted Bite Transfer.

Suneel Belkhale, Ethan K. Gordon, Yuxiao Chen, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Dorsa Sadigh

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Imitation Learning by Estimating Expertise of Demonstrators.

Mark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani

Proceedings of the International Conference on Machine Learning, 2022

Conditional Imitation Learning for Multi-Agent Games.

Andy Shih, Stefano Ermon, Dorsa Sadigh

Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, 2022

APReL: A Library for Active Preference-based Reward Learning Algorithms.

Erdem Biyik, Aditi Talati, Dorsa Sadigh

Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, 2022

Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding.

Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2022

Few-Shot Preference Learning for Human-in-the-Loop RL.

Donald Joseph Hejna III, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2022

Learning Bimanual Scooping Policies for Food Acquisition.

Jennifer Grannen, Yilin Wu, Suneel Belkhale, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2022

Eliciting Compatible Demonstrations for Multi-Human Imitation Learning.

Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2022

PLATO: Predicting Latent Affordances Through Object-Centric Play.

Suneel Belkhale, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2022

PantheonRL: A MARL Library for Dynamic Training Interactions.

Bidipta Sarkar, Aditi Talati, Andy Shih, Dorsa Sadigh

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams.

Erdem Biyik, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Incentivizing Efficient Equilibria in Traffic Networks With Mixed Autonomy.

Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh

IEEE Trans. Control. Netw. Syst., 2021

Learning From Imperfect Demonstrations From Agents With Varying Dynamics.

Zhangjie Cao, Dorsa Sadigh

IEEE Robotics Autom. Lett., 2021

Transfer Reinforcement Learning Across Homotopy Classes.

Zhangjie Cao, Minae Kwon, Dorsa Sadigh

IEEE Robotics Autom. Lett., 2021

From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence.

Nicholas Roy, Ingmar Posner, Tim D. Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Daniel E. Koditschek, Tomás Lozano-Pérez, Vikash Mansinghka, Christopher J. Pal, Blake A. Richards, Dorsa Sadigh, Stefan Schaal, Gaurav S. Sukhatme, Denis Thérien, Marc Toussaint, Michiel van de Panne

CoRR, 2021

Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic.

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

CoRR, 2021

Formalizing and guaranteeing human-robot interaction.

Hadas Kress-Gazit, Kerstin Eder, Guy Hoffman, Henny Admoni, Brenna Argall, Rüdiger Ehlers, Christoffer Heckman, Nils Jansen, Ross A. Knepper, Jan Kretínský, Shelly Levy-Tzedek, Jamy Li, Todd D. Murphey, Laurel D. Riek, Dorsa Sadigh

Commun. ACM, 2021

Influencing leading and following in human-robot teams.

Mengxi Li, Minae Kwon, Dorsa Sadigh

Auton. Robots, 2021

Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality.

Songyuan Zhang, Zhangjie Cao, Dorsa Sadigh, Yanan Sui

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

HyperSPNs: Compact and Expressive Probabilistic Circuits.

Andy Shih, Dorsa Sadigh, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ELLA: Exploration through Learned Language Abstraction.

Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Visually Guided Latent Actions for Assistive Teleoperation.

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

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Cooperative Autonomous Vehicles that Sympathize with Human Drivers.

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

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Emergent Prosociality in Multi-Agent Games Through Gifting.

Woodrow Z. Wang, Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes.

Kejun Li, Maegan Tucker, Erdem Biyik, Ellen R. Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Learning Human Objectives from Sequences of Physical Corrections.

Mengxi Li, Alper Canberk, Dylan P. Losey, Dorsa Sadigh

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Targeted Data Acquisition for Evolving Negotiation Agents.

Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh

Proceedings of the 38th International Conference on Machine Learning, 2021

On the Critical Role of Conventions in Adaptive Human-AI Collaboration.

Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh

Proceedings of the 9th International Conference on Learning Representations, 2021

Incentivizing routing choices for safe and efficient transportation in the face of the COVID-19 pandemic.

Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani

Proceedings of the ICCPS '21: ACM/IEEE 12th International Conference on Cyber-Physical Systems, 2021

Open-domain clarification question generation without question examples.

Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning Reward Functions from Scale Feedback.

Nils Wilde, Erdem Biyik, Dorsa Sadigh, Stephen L. Smith

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Influencing Towards Stable Multi-Agent Interactions.

Woodrow Zhouyuan Wang, Andy Shih, Annie Xie, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Learning Multimodal Rewards from Rankings.

Vivek Myers, Erdem Biyik, Nima Anari, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

LILA: Language-Informed Latent Actions.

Siddharth Karamcheti, Megha Srivastava, Percy Liang, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Learning Feasibility to Imitate Demonstrators with Different Dynamics.

Zhangjie Cao, Yilun Hao, Mengxi Li, Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Efficient and Trustworthy Social Navigation via Explicit and Implicit Robot-Human Communication.

Yuhang Che, Allison M. Okamura, Dorsa Sadigh

IEEE Trans. Robotics, 2020

Learning Adaptive Language Interfaces through Decomposition.

Siddharth Karamcheti, Dorsa Sadigh, Percy Liang

CoRR, 2020

Shared Autonomy with Learned Latent Actions.

Hong Jun Jeon, Dylan P. Losey, Dorsa Sadigh

Proceedings of the Robotics: Science and Systems XVI, 2020

Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving.

Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh

Proceedings of the Robotics: Science and Systems XVI, 2020

Active Preference-Based Gaussian Process Regression for Reward Learning.

Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh

Proceedings of the Robotics: Science and Systems XVI, 2020

Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint.

Malayandi Palan, Shane T. Barratt, Alex McCauley, Dorsa Sadigh, Vikas Sindhwani, Stephen P. Boyd

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Multi-Agent Safe Planning with Gaussian Processes.

Zheqing Zhu, Erdem Biyik, Dorsa Sadigh

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Learning User-Preferred Mappings for Intuitive Robot Control.

Mengxi Li, Dylan P. Losey, Jeannette Bohg, Dorsa Sadigh

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Controlling Assistive Robots with Learned Latent Actions.

Dylan P. Losey, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Dorsa Sadigh

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans.

Minae Kwon, Erdem Biyik, Aditi Talati, Karan Bhasin, Dylan P. Losey, Dorsa Sadigh

Proceedings of the HRI '20: ACM/IEEE International Conference on Human-Robot Interaction, 2020

BLEU Neighbors: A Reference-less Approach to Automatic Evaluation.

Kawin Ethayarajh, Dorsa Sadigh

Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems, 2020

Learning Latent Representations to Influence Multi-Agent Interaction.

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

Proceedings of the 4th Conference on Robot Learning, 2020

Continual Adaptation for Efficient Machine Communication.

Robert X. D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman

Proceedings of the 24th Conference on Computational Natural Language Learning, 2020

Exchangeable Input Representations for Reinforcement Learning.

John Mern, Dorsa Sadigh, Mykel J. Kochenderfer

Proceedings of the 2020 American Control Conference, 2020

2019

Learning How to Dynamically Route Autonomous Vehicles on Shared Roads.

Daniel A. Lazar, Erdem Biyik, Dorsa Sadigh, Ramtin Pedarsani

CoRR, 2019

Batch Active Learning Using Determinantal Point Processes.

Erdem Biyik, Kenneth Wang, Nima Anari, Dorsa Sadigh

CoRR, 2019

Object Exchangeability in Reinforcement Learning: Extended Abstract.

John Mern, Dorsa Sadigh, Mykel J. Kochenderfer

CoRR, 2019

Unsupervised Visuomotor Control through Distributional Planning Networks.

Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn

Proceedings of the Robotics: Science and Systems XV, 2019

Learning Reward Functions by Integrating Human Demonstrations and Preferences.

Malayandi Palan, Gleb Shevchuk, Nicholas Charles Landolfi, Dorsa Sadigh

Proceedings of the Robotics: Science and Systems XV, 2019

Influencing Leading and Following in Human-Robot Teams.

Minae Kwon, Mengxi Li, Alexandre Bucquet, Dorsa Sadigh

Proceedings of the Robotics: Science and Systems XV, 2019

Robots that Take Advantage of Human Trust.

Dylan P. Losey, Dorsa Sadigh

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Active Learning of Reward Dynamics from Hierarchical Queries.

Chandrayee Basu, Erdem Biyik, Zhixun He, Mukesh Singhal, Dorsa Sadigh

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Deep Local Trajectory Replanning and Control for Robot Navigation.

Ashwini Pokle, Roberto Martín-Martín, Patrick Goebel, Vincent Chow, Hans M. Ewald, Junwei Yang, Zhenkai Wang, Amir Sadeghian, Dorsa Sadigh, Silvio Savarese, Marynel Vázquez

Proceedings of the International Conference on Robotics and Automation, 2019

Hierarchical Game-Theoretic Planning for Autonomous Vehicles.

Jaime F. Fisac, Eli Bronstein, Elis Stefansson, Dorsa Sadigh, S. Shankar Sastry, Anca D. Dragan

Proceedings of the International Conference on Robotics and Automation, 2019

Safe and Interactive Autonomy: A Journey Starting from Formal Methods (Keynote).

Dorsa Sadigh

Proceedings of the 2019 Formal Methods in Computer Aided Design, 2019

Human-robot interaction for truck platooning using hierarchical dynamic games.

Elis Stefansson, Jaime F. Fisac, Dorsa Sadigh, S. Shankar Sastry, Karl Henrik Johansson

Proceedings of the 17th European Control Conference, 2019

Learning from My Partner's Actions: Roles in Decentralized Robot Teams.

Dylan P. Losey, Mengxi Li, Jeannette Bohg, Dorsa Sadigh

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Asking Easy Questions: A User-Friendly Approach to Active Reward Learning.

Erdem Biyik, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

The Green Choice: Learning and Influencing Human Decisions on Shared Roads.

Erdem Biyik, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Object Exchangability in Reinforcement Learning.

John Mern, Dorsa Sadigh, Mykel J. Kochenderfer

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models.

Erdem Biyik, Jonathan Margoliash, Shahrouz Ryan Alimo, Dorsa Sadigh

Proceedings of the 2019 American Control Conference, 2019

2018

Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic.

Susmit Jha, Vasumathi Raman, Dorsa Sadigh, Sanjit A. Seshia

J. Autom. Reason., 2018

Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state.

Dorsa Sadigh, Nick Landolfi, Shankar S. Sastry, Sanjit A. Seshia, Anca D. Dragan

Auton. Robots, 2018

Altruistic Autonomy: Beating Congestion on Shared Roads.

Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh

Proceedings of the Algorithmic Foundations of Robotics XIII, 2018

Multi-Agent Generative Adversarial Imitation Learning.

Jiaming Song, Hongyu Ren, Dorsa Sadigh, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Batch Active Preference-Based Learning of Reward Functions.

Erdem Biyik, Dorsa Sadigh

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Maximizing Road Capacity Using Cars that Influence People.

Daniel A. Lazar, Ramtin Pedarsani, Kabir Chandrasekher, Dorsa Sadigh

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

Active Preference-Based Learning of Reward Functions.

Dorsa Sadigh, Anca D. Dragan, Shankar Sastry, Sanjit A. Seshia

Proceedings of the Robotics: Science and Systems XIII, 2017

Stochastic predictive freeway ramp metering from Signal Temporal Logic specifications.

Negar Mehr, Dorsa Sadigh, Roberto Horowitz, S. Shankar Sastry, Sanjit A. Seshia

Proceedings of the 2017 American Control Conference, 2017

2016

Towards Verified Artificial Intelligence.

Sanjit A. Seshia, Dorsa Sadigh

CoRR, 2016

Planning for Autonomous Cars that Leverage Effects on Human Actions.

Dorsa Sadigh, Shankar Sastry, Sanjit A. Seshia, Anca D. Dragan

Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

Safe Control under Uncertainty with Probabilistic Signal Temporal Logic.

Dorsa Sadigh, Ashish Kapoor

Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

Towards trustworthy automation: User interfaces that convey internal and external awareness.

Tara Rezvani, Katherine Rose Driggs-Campbell, Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Ruzena Bajcsy

Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems, 2016

Information gathering actions over human internal state.

Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Anca D. Dragan

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications.

Shromona Ghosh, Dorsa Sadigh, Pierluigi Nuzzo, Vasumathi Raman, Alexandre Donzé, Alberto L. Sangiovanni-Vincentelli, S. Shankar Sastry, Sanjit A. Seshia

Proceedings of the 19th International Conference on Hybrid Systems: Computation and Control, 2016

Probabilistic controller synthesis for freeway traffic networks.

Negar Mehr, Dorsa Sadigh, Roberto Horowitz

Proceedings of the 2016 American Control Conference, 2016

2015

Safe Control under Uncertainty.

Dorsa Sadigh, Ashish Kapoor

CoRR, 2015

Reactive synthesis from signal temporal logic specifications.

Vasumathi Raman, Alexandre Donzé, Dorsa Sadigh, Richard M. Murray, Sanjit A. Seshia

Proceedings of the 18th International Conference on Hybrid Systems: Computation and Control, 2015

Formal methods for semi-autonomous driving.

Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry

Proceedings of the 52nd Annual Design Automation Conference, 2015

2014

Synthesis for Human-in-the-Loop Control Systems.

Wenchao Li, Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia

Proceedings of the Tools and Algorithms for the Construction and Analysis of Systems, 2014

Safety envelope for security.

Ashish Tiwari, Bruno Dutertre, Dejan Jovanovic, Thomas de Candia, Patrick Lincoln, John M. Rushby, Dorsa Sadigh, Sanjit A. Seshia

Proceedings of the 3rd International Conference on High Confidence Networked Systems (part of CPS Week), 2014

User interface design and verification for semi-autonomous driving.

Dorsa Sadigh, Katherine Rose Driggs-Campbell, Ruzena Bajcsy, S. Shankar Sastry, Sanjit A. Seshia

Proceedings of the 3rd International Conference on High Confidence Networked Systems (part of CPS Week), 2014

A learning based approach to control synthesis of Markov decision processes for linear temporal logic specifications.

Dorsa Sadigh, Eric S. Kim, Samuel Coogan, S. Shankar Sastry, Sanjit A. Seshia

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Data-Driven Probabilistic Modeling and Verification of Human Driver Behavior.

Dorsa Sadigh, Katherine Rose Driggs-Campbell, Alberto Puggelli, Wenchao Li, Victor Shia, Ruzena Bajcsy, Alberto L. Sangiovanni-Vincentelli, S. Shankar Sastry, Sanjit A. Seshia

Proceedings of the 2014 AAAI Spring Symposia, 2014

2013

Robust Subspace System Identification via Weighted Nuclear Norm Optimization.

Dorsa Sadigh, Henrik Ohlsson, S. Shankar Sastry, Sanjit A. Seshia

CoRR, 2013

2012

Automating exercise generation: a step towards meeting the MOOC challenge for embedded systems.

Dorsa Sadigh, Sanjit A. Seshia, Mona Gupta

Proceedings of the Workshop on Embedded and Cyber-Physical Systems Education, 2012

2011

Synthesis with Clairvoyance.

Orna Kupferman, Dorsa Sadigh, Sanjit A. Seshia

Proceedings of the Hardware and Software: Verification and Testing, 2011

Timing analysis of interrupt-driven programs under context bounds.

Jonathan Kotker, Dorsa Sadigh, Sanjit A. Seshia

Proceedings of the International Conference on Formal Methods in Computer-Aided Design, 2011