Publications

Probabilistic Inference in the Era of Large Models
Andy Shih
CS Department, Stanford University, March 2024

Ph.D. Dissertation
Efficient Data Collection for Robotic Manipulation via Compositional Generalization
Jensen Gao, Annie Xie, Ted Xiao, Chelsea Finn, Dorsa Sadigh
arxiv, Mar 2024
Imitation Bootstrapped Reinforcement Learning
Hengyuan Hu, Suvir Mirchandani, Dorsa Sadigh
arxiv, Mar 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
arxiv, Mar 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*
arxiv, Mar 2024
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, Dorsa Sadigh
arxiv, Mar 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
arxiv, Mar 2024
SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities
Boyuan Chen, Zhuo Xu, Sean Kirmani, Brian Ichter, Dorsa Sadigh, Leonidas Guibas, Fei Xia
IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024, Jun 2024
Batch Active Learning of Reward Functions from Human Preferences
Erdem Biyik, Nima Anari, Dorsa Sadigh
Journal of Transactions on Human Robotics Interaction, Feb 2024
Physically Grounded Vision-Language Models for Robotic Manipulation
Jensen Gao, Bidipta Sarkar, Fei Xia, Ted Xiao, Jiajun Wu, Brian Ichter, Anirudha Majumdar, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2024
Toward Grounded Commonsense Reasoning
Minae Kwon, Hengyuan Hu, Vivek Myers, Siddharth Karamcheti, Anca Dragan, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2024
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
International Conference on Robotics and Automation (ICRA), May 2024
How to Prompt Your Robot: A Prompt Book for Manipulation Skills with Code as Policies
Montserrat Gonzalez Arenas, Ted Xiao, Sumeet Singh, Vidhi Jain, Allen Z. Ren, Quan Vuong, Jacob Varley, Alexander Herzog, Isabel Leal, Sean Kirmani, Mario Prats, Dorsa Sadigh, Vikas Sindhwani, Kanishka Rao, Jacky Liang, Andy Zeng
International Conference on Robotics and Automation (ICRA), May 2024
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Abhishek Padalkar et al
International Conference on Robotics and Automation (ICRA), May 2024
Contrastive Preference Learning: Learning from Human Feedback without RL
Joey Hejna, Rafael Rafailov*, Harshit Sikchi*, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh
International Conference on Learning Representations (ICLR), May 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
ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2024

Best paper award (technical track).
Scaling Human Feedback
Minae Kwon
CS Department, Stanford University, December 2023

Ph.D. Dissertation
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 Tong Wang, Samuel Marks, Charbel-Raphael Segerie, Micah Carroll, Andi Peng, Phillip 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 Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
Transactions on Machine Learning Research (TMLR)
Parallel Sampling of Diffusion Models
Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari
Conference on Neural Information Processing Systems (NeurIPS), December 2023

Spotlight presentation.
Diverse Conventions for Human-AI Collaboration
Bidipta Sarkar, Andy Shih, Dorsa Sadigh
Conference on Neural Information Processing Systems (NeurIPS), December 2023
Data Quality in Imitation Learning
Suneel Belkhale, Yuchen Cui, Dorsa Sadigh
Conference on Neural Information Processing Systems (NeurIPS), December 2023
Inverse Preference Learning: Preference-based RL without a Reward Function
Joey Hejna, Dorsa Sadigh
Conference on Neural Information Processing Systems (NeurIPS), December 2023
RoboCLIP: One Demonstration is Enough to Learn Robot Policies
Sumedh Anand Sontakke, Seb Arnold, Jesse Zhang, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti
Conference on Neural Information Processing Systems (NeurIPS), December 2023
Active Preference-Based Gaussian Process Regression for Reward Learning and Optimization
Erdem Biyik, Nicolas Huynh, Mykel Kochenderfer, Dorsa Sadigh
The International Journal of Robotics Research (IJRR), September 2023
Stabilize to Act: Learning to Coordinate for Bimanual Manipulation
Jennifer Grannen, Yilin Wu, Brandon Vu, Dorsa Sadigh
Proceedings of the 7th Conference on Robot Learning (CoRL), November 2023

Oral presentation.
HYDRA: Hybrid Robot Actions for Imitation Learning
Suneel Belkhale, Yuchen Cui, Dorsa Sadigh
Proceedings of the 7th Conference on Robot Learning (CoRL), November 2023
Learning Sequential Acquisition Policies for Robot-Assisted Feeding
Priya Sundaresan, Jiajun Wu, Dorsa Sadigh
Proceedings of the 7th Conference on Robot Learning (CoRL), November 2023
Gesture-Informed Robot Assistance via Foundation Model
Li-Heng Lin, Yuchen Cui, Yilun Hao, Fei Xia, Dorsa Sadigh
Proceedings of the 7th Conference on Robot Learning (CoRL), November 2023
KITE: Keypoint-Conditioned Policies for Semantic Manipulation
Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh, Jeannette Bohg
Proceedings of the 7th Conference on Robot Learning (CoRL), November 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 7th Conference on Robot Learning (CoRL), November 2023
Polybot: Training One Policy Across Robots While Embracing Variability
Jonathan Heewon Yang, Dorsa Sadigh, Chelsea Finn
Proceedings of the 7th Conference on Robot Learning (CoRL), November 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 7th Conference on Robot Learning (CoRL), November 2023

Best student paper award, Oral presentation.
Language to Rewards for Robotic Skill Synthesis
Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montse 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 7th Conference on Robot Learning (CoRL), November 2023

Oral presentation.
Robots That Can See: Leveraging Human Pose for Trajectory Prediction
Tim Salzmann, Hao-Tien Chiang, Markus Ryll, Dorsa Sadigh, Carolina Parada, Alex Bewley
IEEE Robotics and Automation Letters (RA-L), September 2023
Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations
Yilun Hao*, Ruinan Wang*, Zhangjie Cao, Zihan Wang, Yuchen Cui, Dorsa Sadigh
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2023

* denotes equal contribution.
Soy: An Efficient MILP Solver for Piecewise-Affine Systems
Haoze Wu, Min Wu, Dorsa Sadigh, Clark Barrett
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2023
Strategic Reasoning with Language Models
Kanishk Gandhi, Dorsa Sadigh, Noah D. Goodman
arxiv, May 2023
Language Instructed Reinforcement Learning for Human-AI Coordination
Hengyuan Hu, Dorsa Sadigh
40th International Conference on Machine Learning (ICML), July 2023
Generating Language Corrections for Teaching Physical Control Tasks
Megha Srivastava, Noah Goodman, Dorsa Sadigh
40th International Conference on Machine Learning (ICML), July 2023
Distance Weighted Supervised Learning for Offline Interaction Data
Joey Hejna, Jensen Gao, Dorsa Sadigh
40th International Conference on Machine Learning (ICML), July 2023
Long Horizon Temperature Scaling
Andy Shih, Dorsa Sadigh, Stefano Ermon
40th International Conference on Machine Learning (ICML), July 2023
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets
Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn
Proceedings of Robotics: Science and Systems (RSS), July 2023
Language-Driven Representation Learning for Robotics
Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang
Proceedings of Robotics: Science and Systems (RSS), July 2023

Best paper award finalist.
Learning to Adapt for Intelligent Robot Behavior
Mengxi Li
Electrical Engineering Department, Stanford University, March 2023

Ph.D. Dissertation
Reward Design with Language Models
Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh
International Conference on Learning Representations (ICLR), May 2023
In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing
Lorenzo Shaikewitz*, Yilin Wu*, Suneel Belkhale*, Jennifer Grannen, Priya Sundaresan, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2023

* denotes equal contribution.
Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation
Mengxi Li, Rika Antonova, Dorsa Sadigh, Jeannette Bohg
International Conference on Robotics and Automation (ICRA), May 2023
Active Reward Learning from Online Preferences
Vivek Myers, Erdem Bıyık, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 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 (HRI), March 2023

* denotes equal contribution.
Learning from Imperfect Demonstrations
Zhangjie Cao
Computer Science Department, Stanford University, December 2022

Ph.D. Dissertation
Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding
Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh
Proceedings of the 6th Conference on Robot Learning (CoRL), December 2022

Oral presentation.
Few-Shot Preference Learning for Human-in-the-Loop RL
Joey Hejna, Dorsa Sadigh
Proceedings of the 6th Conference on Robot Learning (CoRL), December 2022
Eliciting Compatible Demonstrations for Multi-Human Imitation Learning
Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh
Proceedings of the 6th Conference on Robot Learning (CoRL), December 2022
Learning Bimanual Scooping Policies for Food Acquisition
Jennifer Grannen*, Yilin Wu*, Suneel Belkhale, Dorsa Sadigh
Proceedings of the 6th Conference on Robot Learning (CoRL), December 2022

* denotes equal contribution.
PLATO: Predicting Latent Affordances Through Object-Centric Play
Suneel Belkhale, Dorsa Sadigh
Proceedings of the 6th Conference on Robot Learning (CoRL), December 2022
Assistive Teaching of Motor Control Tasks to Humans
Megha Srivastava, Erdem Bıyık, Suvir Mirchandani, Noah Goodman, Dorsa Sadigh
Conference on Neural Information Processing Systems (NeurIPS), November 2022
Training and Inference on Any-Order Autoregressive Models the Right Way
Andy Shih, Dorsa Sadigh, Stefano Ermon
Conference on Neural Information Processing Systems (NeurIPS), November 2022

Oral presentation.
Learning Preferences For Interactive Autonomy
Erdem Bıyık
EE Department, Stanford University, May 2022

Ph.D. Dissertation
Imitation Learning by Estimating Expertise of Demonstrators
Mark Beliaev*, Andy Shih*, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani
39th International Conference on Machine Learning (ICML), July 2022

* denotes equal contribution.
How do People Incorporate Advice from Artificial Agents when Making Physical Judgments?
Erik Brockbank*, Haoliang Wang*, Justin Yang, Suvir Mirchandani, Erdem Bıyık, Dorsa Sadigh, Judith Fan
Cognitive Science Society Conference (CogSci), July 2022

* denotes equal contribution.
Oral presentation.
Shared Autonomy for Robotic Manipulation with Language Corrections
Siddharth Karamcheti*, Raj Palleti*, Yuchen Cui, Percy Liang, Dorsa Sadigh
Workshop on Learning with Natural Language Supervision @ ACL, May 2022

* denotes equal contribution.
Balancing Efficiency and Comfort in Robot-Assisted Bite Transfer
Suneel Belkhale, Ethan Kroll Gordon, Yuxiao Chen, Siddhartha Srinivasa, Tapomayukh Bhattacharjee, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2022
Learning from Imperfect Demonstrations via Adversarial Confidence Transfer
Zhangjie Cao*, Zihan Wang*, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2022

* denotes equal contribution.
Weakly Supervised Correspondence Learning
Zihan Wang*, Zhangjie Cao*, Yilun Hao, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2022

* denotes equal contribution.
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction
Zhangjie Cao, Erdem Bıyık, Guy Rosman, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2022
APReL: A Library for Active Preference-based Reward Learning Algorithms
Erdem Bıyık, Aditi Talati, Dorsa Sadigh
17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2022

Also presented at Artificial Intelligence for Human-Robot Interaction (AI-HRI) at AAAI Fall Symposium Series, November 2021).
Conditional Imitation Learning for Multi-Agent Games
Andy Shih, Stefano Ermon, Dorsa Sadigh
17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2022
PantheonRL: A MARL Library for Dynamic Training Interactions
Bidipta Sarkar*, Aditi Talati*, Andy Shih*, Dorsa Sadigh
Proceedings of the 36th AAAI Conference on Artificial Intelligence (Demo Track), February 2022

* denotes equal contribution.
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams
Erdem Bıyık, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh
Proceedings of the 36th AAAI Conference on Artificial Intelligence, February 2022

Also presented at Artificial Intelligence for Human-Robot Interaction (AI-HRI) at AAAI Fall Symposium Series, November 2021.
Oral presentation.
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints
Shushman Choudhury, Jayesh Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg
Journal of Autonomous Robots (AURO), 2022
Learning Latent Actions to Control Assistive Robots
Dylan Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh
Journal of Autonomous Robots (AURO), 2022
ELLA: Exploration through Learned Language Abstraction
Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh
Conference on Neural Information Processing Systems (NeurIPS), December 2021
Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality
Songyuan Zhang*, Zhangjie Cao*, Dorsa Sadigh, Yanan Sui
Conference on Neural Information Processing Systems (NeurIPS), December 2021

* denotes equal contribution.
HyperSPNs: Compact and Expressive Probabilistic Circuits
Andy Shih, Dorsa Sadigh, Stefano Ermon
Conference on Neural Information Processing Systems (NeurIPS), December 2021
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy, Ingmar Posner, Tim Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Dan Koditschek, Tomas Lozano-Perez, Vikash Mansinghka, Christopher Pal, Blake Richards, Dorsa Sadigh, Stefan Schaal, Gaurav Sukhatme, Denis Therien, Marc Toussaint, Michiel Van de Panne
arXiv, November 2021
LILA: Language-Informed Latent Actions
Siddharth Karamcheti*, Megha Srivastava*, Percy Liang, Dorsa Sadigh
Proceedings of the 5th Conference on Robot Learning (CoRL), November 2021

* denotes equal contribution.
Learning Multimodal Rewards from Rankings
Vivek Myers, Erdem Bıyık, Nima Anari, Dorsa Sadigh
Proceedings of the 5th Conference on Robot Learning (CoRL), November 2021

Oral presentation.
Learning Reward Functions from Scale Feedback
Nils Wilde*, Erdem Bıyık*, Dorsa Sadigh, Stephen L. Smith
Proceedings of the 5th Conference on Robot Learning (CoRL), November 2021

* denotes equal contribution.
Influencing Towards Stable Multi-Agent Interactions
Woodrow Zhouyuan Wang, Andy Shih, Annie Xie, Dorsa Sadigh
Proceedings of the 5th Conference on Robot Learning (CoRL), November 2021

Oral presentation.
Learning Feasibility to Imitate Demonstrators with Different Dynamics
Zhangjie Cao, Yilun Hao, Mengxi Li, Dorsa Sadigh
Proceedings of the 5th Conference on Robot Learning (CoRL), November 2021
Open-domain clarification question generation without question examples
Julia White, Gabriel Poesia, Robert Hawkins, Dorsa Sadigh, Noah Goodman
Conference on Empirical Methods in Natural Language Processing (EMNLP), November 2021
Formalizing and Guaranteeing* Human-Robot Interaction
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
Communications of the ACM (CACM), September 2021
Influencing Leading and Following in Human-Robot Teams
Mengxi Li*, Minae Kwon*, Dorsa Sadigh
Journal of Autonomous Robots (AURO), 2021
Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences
Erdem Bıyık, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh
The International Journal of Robotics Research (IJRR), 2021
Learning How to Dynamically Route Autonomous Vehicles on Shared Roads
Daniel A. Lazar*, Erdem Bıyık*, Dorsa Sadigh, Ramtin Pedarsani
Transportation Research Part C: Emerging Technologies (TR_C), September 2021

* denotes equal contribution.
Cooperative Autonomous Vehicles that Sympathize with Human Drivers
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser Fallah
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2021
Emergent Prosociality in Multi-Agent Games Through Gifting
Woodrow Z. Wang*, Mark Beliaev*, Erdem Bıyık*, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh
30th International Joint Conference on Artificial Intelligence (IJCAI), August 2021

* denotes equal contribution.
Targeted Data Acquisition for Evolving Negotiation Agents
Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuéllar, Dorsa Sadigh
38th International Conference on Machine Learning (ICML), July 2021
Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy
Erdem Bıyık*, Daniel A. Lazar*, Ramtin Pedarsani, Dorsa Sadigh
IEEE Transactions on Control of Network Systems (TCNS), 2021

* denotes equal contribution.
Learning from Imperfect Demonstrations from Agents with Varying Dynamics
Zhangjie Cao, Dorsa Sadigh
IEEE Robotics and Automation Letters (RA-L), July 2021

Also presented at ICRA 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
CVPR 2021 Workshop on Autonomous Driving: Perception, Prediction and Planning, June 2021
Learning Visually Guided Latent Actions for Assistive Teleoperation
Siddharth Karamcheti, Albert J. Zhai, Dylan P. Losey, Dorsa Sadigh
3rd Annual Learning for Dynamics & Control Conference (L4DC), June 2021
Learning Human Objectives from Sequences of Physical Corrections
Mengxi Li, Alper Canberk, Dylan P. Losey, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2021
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes
Kejun Li, Maegan Tucker, Erdem Bıyık, Ellen Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames
International Conference on Robotics and Automation (ICRA), May 2021
Transfer Reinforcement Learning across Homotopy Classes
Zhangjie Cao*, Minae Kwon*, Dorsa Sadigh
IEEE Robotics and Automation Letters (RA-L), February 2021

* denotes equal contribution. Also presented at ICRA 2021.
Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic
Mark Beliaev, Erdem Bıyık, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani
12th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), May 2021
On the Critical Role of Conventions in Adaptive Human-AI Collaboration
Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh
9th International Conference on Learning Representations (ICLR), May 2021
Learning Latent Representations to Influence Multi-Agent Interaction
Annie Xie, Dylan Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh
Proceedings of the 4th Conference on Robot Learning (CoRL), November 2020

Best paper award winner and oral presentation.
Learning Adaptive Language Interfaces through Decomposition
Siddharth Karamcheti, Dorsa Sadigh, Percy Liang
Workshop on Interactive and Executable Semantic Parsing @ EMNLP, November 2020
Continual Adaptation for Efficient Machine Communication
Robert Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman
24th Conference on Computational Natural Language Learning (CoNLL 2020), November 2020

Also best paper award winner at ICML 2019 Workshop on Adaptive & Multitask Learning: Algorithms & Systems (PDF).
BLEU Neighbors: A Reference-less Approach to Automatic Evaluation
Kawin Ethayarajh, Dorsa Sadigh
1st Workshop on Evaluation and Comparison for NLP systems (Eval4NLP), November 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 (IROS), October 2020
Multi-Agent Safe Planning with Gaussian Processes
Zheqing Zhu, Erdem Bıyık, Dorsa Sadigh
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020
Active Preference-Based Gaussian Process Regression for Reward Learning
Erdem Bıyık*, Nicolas Huynh*, Mykel J. Kochenderfer, Dorsa Sadigh
Proceedings of Robotics: Science and Systems (RSS), July 2020

* denotes equal contribution.
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving
Zhangjie Cao*, Erdem Bıyık*, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh
Proceedings of Robotics: Science and Systems (RSS), July 2020

* denotes equal contribution.
Shared Autonomy with Learned Latent Actions
Hong Jun Jeon, Dylan Losey, Dorsa Sadigh
Proceedings of Robotics: Science and Systems (RSS), July 2020

Best student paper award finalist.
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints
Shushman Choudhury, Jayesh Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg
Proceedings of Robotics: Science and Systems (RSS), July 2020
Emergent Correlated Equilibrium through Synchronized Exploration
Mark Beliaev*, Woodrow Z. Wang*, Daniel A. Lazar, Erdem Bıyık, Dorsa Sadigh, Ramtin Pedarsani
RSS 2020 Workshop on Emergent Behaviors in Human-Robot Systems, July 2020
Exchangeable Input Representations for Reinforcement Learning
John Mern, Dorsa Sadigh, Mykel J. Kochenderfer
Proceedings of the American Control Conference (ACC), July 2020

Also presented at the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2019, as an Extended Abstract.
Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint
Malayandi Palan*, Shane Barratt*, Alex McCauley, Dorsa Sadigh, Vikas Sindhwani, Stephen P. Boyd
2nd Learning for Dynamics & Control Conference (L4DC), June 2020

* denotes equal contribution.
Efficient and Trustworthy Social Navigation Via Explicit and Implicit Robot-Human Communication
Yuhang Che, Allison M. Okamura, Dorsa Sadigh
IEEE Transactions on Robotics (T-RO), June 2020
Controlling Assistive Robots with Learned Latent Actions
Dylan P. Losey, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2020
When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans
Minae Kwon, Erdem Bıyık, Aditi Talati, Karan Bhasin, Dylan P. Losey, Dorsa Sadigh
ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2020

Also presented at Cooperative AI NeurIPS Workshop 2021, December 2021 (PDF).
Honorable mention award.
The Green Choice: Learning and Influencing Human Decisions on Shared Roads
Erdem Bıyık, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani
Proceedings of the 58th IEEE Conference on Decision and Control (CDC), December 2019
Active Learning of Reward Dynamics from Hierarchical Queries
Chandrayee Basu, Erdem Bıyık, Zhixun He, Mukesh Singhal, Dorsa Sadigh
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019
Robots that Take Advantage of Human Trust
Dylan P. Losey, Dorsa Sadigh
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019
Asking Easy Questions: A User-Friendly Approach to Active Reward Learning
Erdem Bıyık, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh
Proceedings of the 3rd Conference on Robot Learning (CoRL), October 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 Conference on Robot Learning (CoRL), October 2019

* denotes equal contribution.
Oral presentation.
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models
Erdem Bıyık*, Jonathan Margoliash*, Shahrouz R. Alimo, Dorsa Sadigh
Proceedings of the American Control Conference (ACC), July 2019

* denotes equal contribution.
Human-Robot Interaction for Truck Platooning Using Hierarchical Dynamic Games
Elis Stefansson, Jaime Fisac, Dorsa Sadigh, Shankar Sastry, Karl H. Johansson
European Control Conference (ECC), June 2019

Best student paper award finalist.
Influencing Leading and Following in Human-Robot Teams
Minae Kwon*, Mengxi Li*, Alexandre Bucquet, Dorsa Sadigh
Proceedings of Robotics: Science and Systems (RSS), June 2019

* denotes equal contribution.
Learning Reward Functions by Integrating Human Demonstrations and Preferences
Malayandi Palan*, Nicholas C. Landolfi*, Gleb Shevchuk, Dorsa Sadigh
Proceedings of Robotics: Science and Systems (RSS), June 2019

* denotes equal contribution.
Unsupervised Visuomotor Control through Distributional Planning Networks
Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn
Proceedings of Robotics: Science and Systems (RSS), June 2019

Also presented at ICML Workshop on Self-Supervised Learning, and at ICML Workshop on Imitation, Intent, and Interaction (I3), June 2019 (PDF).
Batch Active Learning Using Determinantal Point Processes
Erdem Bıyık, Kenneth Wang, Nima Anari, Dorsa Sadigh
arXiv preprint, June 2019
Deep Local Trajectory Replanning and Control for Robot Navigation
Ashwini Pokle, Roberto Martín-Martín, Patrick Goebel, Vincent Chow, Hans Magnus Ewald, Junwei Yang, Wang Zhenkai, Amir Sadeghian, Dorsa Sadigh, Silvio Savarese, Marynel Vázquez
International Conference on Robotics and Automation (ICRA), May 2019
Hierarchical Game-Theoretic Planning for Autonomous Vehicles
Jaime F. Fisac*, Eli Bronstein*, Elis Stefansson, Dorsa Sadigh, S. Shankar Sastry, Anca D. Dragan
International Conference on Robotics and Automation (ICRA), May 2019

* denotes equal contribution.
Maximizing Road Capacity Using Cars that Influence People
Daniel A. Lazar, Kabir Chandrasekher, Ramtin Pedarsani, Dorsa Sadigh
Proceedings of the 57th IEEE Conference on Decision and Control (CDC), December 2018
Verifying Robustness of Human-Aware Autonomous Cars
Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia
Proceedings of the 2nd IFAC Conference on Cyber-Physical and Human Systems, December 2018
Altruistic Autonomy: Beating Congestion on Shared Roads
Erdem Bıyık*, Daniel A. Lazar*, Ramtin Pedarsani, Dorsa Sadigh
Proceedings of the 13th International Workshop on Algorithmic Foundations of Robotics (WAFR), December 2018

* denotes equal contribution.
Multi-Agent Generative Adversarial Imitation Learning
Jiaming Song, Hongyu Ren, Dorsa Sadigh, Stefano Ermon
Advances in Neural Information Processing Systems (NIPS), December 2018

Also presented at International Conference on Learning Representations (ICLR), Workshop Track, April 2018 (PDF).
Batch Active Preference-Based Learning of Reward Functions
Erdem Bıyık, Dorsa Sadigh
Proceedings of the 2nd Conference on Robot Learning (CoRL), October 2018

Oral presentation.
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, S. Shankar Sastry, Sanjit A. Seshia, Anca D. Dragan
Autonomous Robots (AURO), October 2018
Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic
Susmit Jha, Vasumathi Raman, Dorsa Sadigh, Sanjit A. Seshia
Journal of Automated Reasoning (JAR), January 2018
Safe and Interactive Autonomy: Control, Learning, and Verification
Dorsa Sadigh
EECS Department, University of California, Berkeley, August 2017

Ph.D. Dissertation
Active Preference-Based Learning of Reward Functions
Dorsa Sadigh, Anca D. Dragan, S. Shankar Sastry, Sanjit A. Seshia
Proceedings of Robotics: Science and Systems (RSS), July 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 American Control Conference (ACC), May 2017
Towards Trustworthy Automation: User Interfaces that Convey Internal and External Awareness
Tara Rezvani, Katherine Driggs-Campbell, Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Ruzena Bajcsy
Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC), November 2016
Information Gathering Actions over Human Internal State
Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Anca Dragan
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2016

Best paper in cognitive robotics award finalist.
Safe Control Under Uncertainty with Probabilistic Signal Temporal Logic
Dorsa Sadigh, Ashish Kapoor
Proceedings of Robotics: Science and Systems (RSS), June 2016
Planning for Autonomous Cars that Leverage Effects on Human Actions
Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Anca D. Dragan
Proceedings of Robotics: Science and Systems (RSS), June 2016
Towards Verified Artificial Intelligence
Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry
Technical Report, July 2016
Fast Safe Mission Plans for Autonomous Vehicles
Debadeepta Dey, Dorsa Sadigh, Ashish Kapoor
Proceedings of Robotics: Science and Systems Workshop, June 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 (HSCC), April 2016
Formal Methods for Semi-Autonomous Driving
Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry
Proceedings of the Design Automation Conference (DAC), June 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 (HSCC), April 2015
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 (CDC), December 2014
Robust Subspace System Identification via Weighted Nuclear Norm Optimization
Dorsa Sadigh, Henrik Ohlsson, Sanjit A. Seshia, S. Shankar Sastry
Proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC), August 2014
Safety Envelope for Security
Ashish Tiwari, Bruno Dutertre, Dejan Jovanović, Thomas de Candia, Patrick D. Lincoln, John Rushby, Dorsa Sadigh, Sanjit A. Seshia
Proceedings of the 3rd International Conference on High Confidence Networked Systems (HiCoNS), April 2014
User Interface Design and Verification for Semi-Autonomous Driving
Dorsa Sadigh, Katherine Driggs-Campbell, Ruzena Bajcsy, S. Shankar Sastry, Sanjit A. Seshia
Proceedings of the 3rd International Conference on High Confidence Networked Systems (HiCoNS), April 2014
Data-Driven Probabilistic Modeling and Verification of Human Driver Behavior
Dorsa Sadigh, Katherine Driggs-Campbell, Alberto Puggelli, Wenchao Li, Victor Shia, Ruzena Bajcsy, Alberto L. Sangiovanni-Vincentelli, S. Shankar Sastry, Sanjit A. Seshia
Proceedings of the AAAI Spring Symposium on Formal Verification and Modeling in Human-Machine Systems, March 2014
Synthesis for Human-in-the-Loop Control Systems
Wenchao Li, Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia
Proceedings of the 20th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), March 2014
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 (WESE), October 2012
Synthesis with Clairvoyance
Orna Kupferman, Dorsa Sadigh, Sanjit A. Seshia
Proceedings of the Haifa Verification Conference (HVC), December 2011
Timing Analysis of Interrupt-Driven Programs under Context Bounds
Jonathan Kotker, Dorsa Sadigh, Sanjit A. Seshia
Proceedings of the IEEE International Conference on Formal Methods in Computer-Aided Design (FMCAD), October 2011