Timing analysis of interrupt-driven programs under context bounds. - Jonathan Kotker; Dorsa Sadigh; Sanjit A. Seshia (FMCAD, 2011)

Synthesis with Clairvoyance. - Orna Kupferman; Dorsa Sadigh; Sanjit A. Seshia (Haifa Verification Conference, 2011)

Automating exercise generation: a step towards meeting the MOOC challenge for embedded systems. - Dorsa Sadigh; Sanjit A. Seshia; Mona Gupta (WESE, 2012)

Robust Subspace System Identification via Weighted Nuclear Norm Optimization. - Dorsa Sadigh; Henrik Ohlsson; S. Shankar Sastry; Sanjit A. Seshia (CoRR, 2013)

Data-Driven Probabilistic Modeling and Verification of Human Driver Behavior. - Dorsa Sadigh; Katherine Rose Driggs-Campbell; Alberto Puggelli; Wenchao Li 001; Victor Shia; Ruzena Bajcsy; Alberto L. Sangiovanni-Vincentelli; S. Shankar Sastry; Sanjit A. Seshia (AAAI Spring Symposia, 2014)

A learning based approach to control synthesis of Markov decision processes for linear temporal logic specifications. - Dorsa Sadigh; Eric S. Kim; Samuel Coogan 001; S. Shankar Sastry; Sanjit A. Seshia (CDC, 2014)

User interface design and verification for semi-autonomous driving. - Dorsa Sadigh; Katherine Rose Driggs-Campbell; Ruzena Bajcsy; S. Shankar Sastry; Sanjit A. Seshia (HiCoNS, 2014)

Safety envelope for security. - Ashish Tiwari 001; Bruno Dutertre; Dejan Jovanovic; Thomas de Candia; Patrick Lincoln; John M. Rushby; Dorsa Sadigh; Sanjit A. Seshia (HiCoNS, 2014)

Synthesis for Human-in-the-Loop Control Systems. - Wenchao Li 001; Dorsa Sadigh; S. Shankar Sastry; Sanjit A. Seshia (TACAS, 2014)

Formal methods for semi-autonomous driving. - Sanjit A. Seshia; Dorsa Sadigh; S. Shankar Sastry (DAC, 2015)

Reactive synthesis from signal temporal logic specifications. - Vasumathi Raman; Alexandre Donzé; Dorsa Sadigh; Richard M. Murray; Sanjit A. Seshia (HSCC, 2015)

Safe Control under Uncertainty. - Dorsa Sadigh; Ashish Kapoor (CoRR, 2015)

Probabilistic controller synthesis for freeway traffic networks. - Negar Mehr; Dorsa Sadigh; Roberto Horowitz (ACC, 2016)

Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications. - Shromona Ghosh; Dorsa Sadigh; Pierluigi Nuzzo 002; Vasumathi Raman; Alexandre Donzé; Alberto L. Sangiovanni-Vincentelli; S. Shankar Sastry; Sanjit A. Seshia (HSCC, 2016)

Information gathering actions over human internal state. - Dorsa Sadigh; S. Shankar Sastry; Sanjit A. Seshia; Anca D. Dragan (IROS, 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 (ITSC, 2016)

Safe Control under Uncertainty with Probabilistic Signal Temporal Logic. - Dorsa Sadigh; Ashish Kapoor (Robotics: Science and Systems, 2016)

Planning for Autonomous Cars that Leverage Effects on Human Actions. - Dorsa Sadigh; Shankar Sastry 001; Sanjit A. Seshia; Anca D. Dragan (Robotics: Science and Systems, 2016)

Towards Verified Artificial Intelligence. - Sanjit A. Seshia; Dorsa Sadigh (CoRR, 2016)

Stochastic predictive freeway ramp metering from Signal Temporal Logic specifications. - Negar Mehr; Dorsa Sadigh; Roberto Horowitz; S. Shankar Sastry; Sanjit A. Seshia (ACC, 2017)

Active Preference-Based Learning of Reward Functions. - Dorsa Sadigh; Anca D. Dragan; Shankar Sastry 001; Sanjit A. Seshia (Robotics: Science and Systems, 2017)

Maximizing Road Capacity Using Cars that Influence People. - Daniel A. Lazar; Ramtin Pedarsani; Kabir Chandrasekher; Dorsa Sadigh (CDC, 2018)

Batch Active Preference-Based Learning of Reward Functions. - Erdem Biyik; Dorsa Sadigh (CoRL, 2018)

Multi-Agent Generative Adversarial Imitation Learning. - Jiaming Song; Hongyu Ren; Dorsa Sadigh; Stefano Ermon (NeurIPS, 2018)

Altruistic Autonomy: Beating Congestion on Shared Roads. - Erdem Biyik; Daniel A. Lazar; Ramtin Pedarsani; Dorsa Sadigh (WAFR, 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)

Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic. - Susmit Jha; Vasumathi Raman; Dorsa Sadigh; Sanjit A. Seshia (J. Autom. Reason., 2018)

Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models. - Erdem Biyik; Jonathan Margoliash; Shahrouz Ryan Alimo; Dorsa Sadigh (ACC, 2019)

Object Exchangability in Reinforcement Learning. - John Mern; Dorsa Sadigh; Mykel J. Kochenderfer (AAMAS, 2019)

The Green Choice: Learning and Influencing Human Decisions on Shared Roads. - Erdem Biyik; Daniel A. Lazar; Dorsa Sadigh; Ramtin Pedarsani (CDC, 2019)

Asking Easy Questions: A User-Friendly Approach to Active Reward Learning. - Erdem Biyik; Malayandi Palan; Nicholas C. Landolfi; Dylan P. Losey; Dorsa Sadigh (CoRL, 2019)

Learning from My Partner's Actions: Roles in Decentralized Robot Teams. - Dylan P. Losey; Mengxi Li; Jeannette Bohg; Dorsa Sadigh (CoRL, 2019)

Human-robot interaction for truck platooning using hierarchical dynamic games. - Elis Stefansson; Jaime F. Fisac; Dorsa Sadigh; S. Shankar Sastry; Karl Henrik Johansson (ECC, 2019)

Safe and Interactive Autonomy: A Journey Starting from Formal Methods (Keynote). - Dorsa Sadigh (FMCAD, 2019)

Hierarchical Game-Theoretic Planning for Autonomous Vehicles. - Jaime F. Fisac; Eli Bronstein; Elis Stefansson; Dorsa Sadigh; S. Shankar Sastry; Anca D. Dragan (ICRA, 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 (ICRA, 2019)

Active Learning of Reward Dynamics from Hierarchical Queries. - Chandrayee Basu; Erdem Biyik; Zhixun He; Mukesh Singhal; Dorsa Sadigh (IROS, 2019)

Robots that Take Advantage of Human Trust. - Dylan P. Losey; Dorsa Sadigh (IROS, 2019)

Influencing Leading and Following in Human-Robot Teams. - Minae Kwon; Mengxi Li; Alexandre Bucquet; Dorsa Sadigh (Robotics: Science and Systems, 2019)

Learning Reward Functions by Integrating Human Demonstrations and Preferences. - Malayandi Palan; Gleb Shevchuk; Nicholas Charles Landolfi; Dorsa Sadigh (Robotics: Science and Systems, 2019)

Unsupervised Visuomotor Control through Distributional Planning Networks. - Tianhe Yu; Gleb Shevchuk; Dorsa Sadigh; Chelsea Finn (Robotics: Science and Systems, 2019)

Object Exchangeability in Reinforcement Learning: Extended Abstract. - John Mern; Dorsa Sadigh; Mykel J. Kochenderfer (CoRR, 2019)

Batch Active Learning Using Determinantal Point Processes. - Erdem Biyik; Kenneth Wang 003; Nima Anari; Dorsa Sadigh (CoRR, 2019)

Learning How to Dynamically Route Autonomous Vehicles on Shared Roads. - Daniel A. Lazar; Erdem Biyik; Dorsa Sadigh; Ramtin Pedarsani (CoRR, 2019)

Exchangeable Input Representations for Reinforcement Learning. - John Mern; Dorsa Sadigh; Mykel J. Kochenderfer (ACC, 2020)

Continual Adaptation for Efficient Machine Communication. - Robert X. D. Hawkins; Minae Kwon; Dorsa Sadigh; Noah D. Goodman (CoNLL, 2020)

Learning Latent Representations to Influence Multi-Agent Interaction. - Annie Xie; Dylan P. Losey; Ryan Tolsma; Chelsea Finn; Dorsa Sadigh (CoRL, 2020)

BLEU Neighbors: A Reference-less Approach to Automatic Evaluation. - Kawin Ethayarajh; Dorsa Sadigh (Eval4NLP, 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 (HRI, 2020)

Controlling Assistive Robots with Learned Latent Actions. - Dylan P. Losey; Krishnan Srinivasan; Ajay Mandlekar; Animesh Garg; Dorsa Sadigh (ICRA, 2020)

Learning User-Preferred Mappings for Intuitive Robot Control. - Mengxi Li; Dylan P. Losey; Jeannette Bohg; Dorsa Sadigh (IROS, 2020)

Multi-Agent Safe Planning with Gaussian Processes. - Zheqing Zhu; Erdem Biyik; Dorsa Sadigh (IROS, 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 (L4DC, 2020)

Active Preference-Based Gaussian Process Regression for Reward Learning. - Erdem Biyik; Nicolas Huynh; Mykel J. Kochenderfer; Dorsa Sadigh (Robotics: Science and Systems, 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 (Robotics: Science and Systems, 2020)

Shared Autonomy with Learned Latent Actions. - Hong Jun Jeon; Dylan P. Losey; Dorsa Sadigh (Robotics: Science and Systems, 2020)

Learning Adaptive Language Interfaces through Decomposition. - Siddharth Karamcheti; Dorsa Sadigh; Percy Liang (CoRR, 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 Feasibility to Imitate Demonstrators with Different Dynamics. - Zhangjie Cao; Yilun Hao; Mengxi Li; Dorsa Sadigh (CoRL, 2021)

LILA: Language-Informed Latent Actions. - Siddharth Karamcheti; Megha Srivastava; Percy Liang; Dorsa Sadigh (CoRL, 2021)

Learning Multimodal Rewards from Rankings. - Vivek Myers; Erdem Biyik; Nima Anari; Dorsa Sadigh (CoRL, 2021)

Influencing Towards Stable Multi-Agent Interactions. - Woodrow Zhouyuan Wang; Andy Shih; Annie Xie; Dorsa Sadigh (CoRL, 2021)

Learning Reward Functions from Scale Feedback. - Nils Wilde; Erdem Biyik; Dorsa Sadigh; Stephen L. Smith 001 (CoRL, 2021)

Open-domain clarification question generation without question examples. - Julia White 001; Gabriel Poesia; Robert X. D. Hawkins; Dorsa Sadigh; Noah D. Goodman (EMNLP (1), 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 (ICCPS, 2021)

On the Critical Role of Conventions in Adaptive Human-AI Collaboration. - Andy Shih; Arjun Sawhney; Jovana Kondic; Stefano Ermon; Dorsa Sadigh (ICLR, 2021)

Targeted Data Acquisition for Evolving Negotiation Agents. - Minae Kwon; Siddharth Karamcheti; Mariano-Florentino Cuellar; Dorsa Sadigh (ICML, 2021)

Learning Human Objectives from Sequences of Physical Corrections. - Mengxi Li; Alper Canberk; Dylan P. Losey; Dorsa Sadigh (ICRA, 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 (ICRA, 2021)

Emergent Prosociality in Multi-Agent Games Through Gifting. - Woodrow Z. Wang; Mark Beliaev; Erdem Biyik; Daniel A. Lazar; Ramtin Pedarsani; Dorsa Sadigh (IJCAI, 2021)

Cooperative Autonomous Vehicles that Sympathize with Human Drivers. - Behrad Toghi; Rodolfo Valiente; Dorsa Sadigh; Ramtin Pedarsani; Yaser P. Fallah (IROS, 2021)

Learning Visually Guided Latent Actions for Assistive Teleoperation. - Siddharth Karamcheti; Albert J. Zhai; Dylan P. Losey; Dorsa Sadigh (L4DC, 2021)

ELLA: Exploration through Learned Language Abstraction. - Suvir Mirchandani; Siddharth Karamcheti; Dorsa Sadigh (NeurIPS, 2021)

HyperSPNs: Compact and Expressive Probabilistic Circuits. - Andy Shih; Dorsa Sadigh; Stefano Ermon (NeurIPS, 2021)

Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality. - Songyuan Zhang; Zhangjie Cao; Dorsa Sadigh; Yanan Sui (NeurIPS, 2021)

Influencing leading and following in human-robot teams. - Mengxi Li; Minae Kwon; Dorsa Sadigh (Auton. Robots, 2021)

Formalizing and guaranteeing human-robot interaction. - Hadas Kress-Gazit; Kerstin Eder; Guy Hoffman; Henny Admoni; Brenna Argall; Rüdiger Ehlers; Christoffer Heckman; Nils Jansen 001; Ross A. Knepper; Jan Kretínský; Shelly Levy-Tzedek; Jamy Li; et al. (Commun. ACM, 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)

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 001; et al. (CoRR, 2021)

Transfer Reinforcement Learning Across Homotopy Classes. - Zhangjie Cao; Minae Kwon; Dorsa Sadigh (IEEE Robotics Autom. Lett., 2021)

Learning From Imperfect Demonstrations From Agents With Varying Dynamics. - Zhangjie Cao; Dorsa Sadigh (IEEE Robotics Autom. Lett., 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)

Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams. - Erdem Biyik; Anusha Lalitha; Rajarshi Saha; Andrea Goldsmith; Dorsa Sadigh (AAAI, 2022)

PantheonRL: A MARL Library for Dynamic Training Interactions. - Bidipta Sarkar; Aditi Talati; Andy Shih; Dorsa Sadigh (AAAI, 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 (CogSci, 2022)

PLATO: Predicting Latent Affordances Through Object-Centric Play. - Suneel Belkhale; Dorsa Sadigh (CoRL, 2022)

Eliciting Compatible Demonstrations for Multi-Human Imitation Learning. - Kanishk Gandhi; Siddharth Karamcheti; Madeline Liao; Dorsa Sadigh (CoRL, 2022)

Learning Bimanual Scooping Policies for Food Acquisition. - Jennifer Grannen; Yilin Wu 003; Suneel Belkhale; Dorsa Sadigh (CoRL, 2022)

Few-Shot Preference Learning for Human-in-the-Loop RL. - Donald Joseph Hejna III; Dorsa Sadigh (CoRL, 2022)

Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding. - Priya Sundaresan; Suneel Belkhale; Dorsa Sadigh (CoRL, 2022)

APReL: A Library for Active Preference-based Reward Learning Algorithms. - Erdem Biyik; Aditi Talati; Dorsa Sadigh (HRI, 2022)

Conditional Imitation Learning for Multi-Agent Games. - Andy Shih; Stefano Ermon; Dorsa Sadigh (HRI, 2022)

Imitation Learning by Estimating Expertise of Demonstrators. - Mark Beliaev; Andy Shih; Stefano Ermon; Dorsa Sadigh; Ramtin Pedarsani (ICML, 2022)

Balancing Efficiency and Comfort in Robot-Assisted Bite Transfer. - Suneel Belkhale; Ethan K. Gordon; Yuxiao Chen 006; Siddhartha S. Srinivasa; Tapomayukh Bhattacharjee; Dorsa Sadigh (ICRA, 2022)

Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction. - Zhangjie Cao; Erdem Biyik; Guy Rosman; Dorsa Sadigh (ICRA, 2022)

Learning from Imperfect Demonstrations via Adversarial Confidence Transfer. - Zhangjie Cao; Zihan Wang; Dorsa Sadigh (ICRA, 2022)

Weakly Supervised Correspondence Learning. - Zihan Wang; Zhangjie Cao; Yilun Hao; Dorsa Sadigh (ICRA, 2022)

Training and Inference on Any-Order Autoregressive Models the Right Way. - Andy Shih; Dorsa Sadigh; Stefano Ermon (NeurIPS, 2022)

Assistive Teaching of Motor Control Tasks to Humans. - Megha Srivastava; Erdem Biyik; Suvir Mirchandani; Noah D. Goodman; Dorsa Sadigh (NeurIPS, 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)

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)

Toward verified artificial intelligence. - Sanjit A. Seshia; Dorsa Sadigh; S. Shankar Sastry (Commun. ACM, 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)

Social Coordination and Altruism in Autonomous Driving. - Behrad Toghi; Rodolfo Valiente; Dorsa Sadigh; Ramtin Pedarsani; Yaser P. Fallah (IEEE Trans. Intell. Transp. Syst., 2022)

Interactive Learning and Control in the Era of Large Models. - Dorsa Sadigh (CDC, 2023)

Language to Rewards for Robotic Skill Synthesis. - Wenhao Yu 003; 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; et al. (CoRL, 2023)

HYDRA: Hybrid Robot Actions for Imitation Learning. - Suneel Belkhale; Yuchen Cui; Dorsa Sadigh (CoRL, 2023)

Stabilize to Act: Learning to Coordinate for Bimanual Manipulation. - Jennifer Grannen; Yilin Wu 003; Brandon Vu; Dorsa Sadigh (CoRL, 2023)

Gesture-Informed Robot Assistance via Foundation Models. - Li-Heng Lin; Yuchen Cui; Yilun Hao; Fei Xia 002; Dorsa Sadigh (CoRL, 2023)

Large Language Models as General Pattern Machines. - Suvir Mirchandani; Fei Xia 002; Pete Florence; Brian Ichter; Danny Driess; Montserrat Gonzalez Arenas; Kanishka Rao; Dorsa Sadigh; Andy Zeng 001 (CoRL, 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 010; Leila Takayama; Fei Xia 002; Jake Varley; Zhenjia Xu; Dorsa Sadigh; et al. (CoRL, 2023)

Learning Sequential Acquisition Policies for Robot-Assisted Feeding. - Priya Sundaresan; Jiajun Wu 001; Dorsa Sadigh (CoRL, 2023)

KITE: Keypoint-Conditioned Policies for Semantic Manipulation. - Priya Sundaresan; Suneel Belkhale; Dorsa Sadigh; Jeannette Bohg (CoRL, 2023)

Polybot: Training One Policy Across Robots While Embracing Variability. - Jonathan Heewon Yang; Dorsa Sadigh; Chelsea Finn (CoRL, 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 (HRI, 2023)

Reward Design with Language Models. - Minae Kwon; Sang Michael Xie; Kalesha Bullard; Dorsa Sadigh (ICLR, 2023)

Distance Weighted Supervised Learning for Offline Interaction Data. - Joey Hejna; Jensen Gao; Dorsa Sadigh (ICML, 2023)

Language Instructed Reinforcement Learning for Human-AI Coordination. - Hengyuan Hu; Dorsa Sadigh (ICML, 2023)

Long Horizon Temperature Scaling. - Andy Shih; Dorsa Sadigh; Stefano Ermon (ICML, 2023)

Generating Language Corrections for Teaching Physical Control Tasks. - Megha Srivastava; Noah D. Goodman; Dorsa Sadigh (ICML, 2023)

Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation. - Mengxi Li; Rika Antonova; Dorsa Sadigh; Jeannette Bohg (ICRA, 2023)

Active Reward Learning from Online Preferences. - Vivek Myers; Erdem Biyik; Dorsa Sadigh (ICRA, 2023)

In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing. - Lorenzo Shaikewitz; Yilin Wu 003; Suneel Belkhale; Jennifer Grannen; Priya Sundaresan; Dorsa Sadigh (ICRA, 2023)

Soy: An Efficient MILP Solver for Piecewise-Affine Systems. - Haoze Wu 001; Min Wu; Dorsa Sadigh; Clark W. Barrett (IROS, 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)

Data Quality in Imitation Learning. - Suneel Belkhale; Yuchen Cui; Dorsa Sadigh (NeurIPS, 2023)

Inverse Preference Learning: Preference-based RL without a Reward Function. - Joey Hejna; Dorsa Sadigh (NeurIPS, 2023)

Diverse Conventions for Human-AI Collaboration. - Bidipta Sarkar; Andy Shih; Dorsa Sadigh (NeurIPS, 2023)

Parallel Sampling of Diffusion Models. - Andy Shih; Suneel Belkhale; Stefano Ermon; Dorsa Sadigh; Nima Anari (NeurIPS, 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 (NeurIPS, 2023)

Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets. - Maximilian Du; Suraj Nair 003; Dorsa Sadigh; Chelsea Finn (Robotics: Science and Systems, 2023)

Language-Driven Representation Learning for Robotics. - Siddharth Karamcheti; Suraj Nair 003; Annie S. Chen; Thomas Kollar; Chelsea Finn; Dorsa Sadigh; Percy Liang (Robotics: Science and Systems, 2023)

Strategic Reasoning with Language Models. - Kanishk Gandhi; Dorsa Sadigh; Noah D. Goodman (CoRR, 2023)

Toward Grounded Social Reasoning. - Minae Kwon; Hengyuan Hu; Vivek Myers; Siddharth Karamcheti; Anca D. Dragan; Dorsa Sadigh (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)

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; et al. (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 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; et al. (Trans. Mach. Learn. Res., 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., 2023)

Vocal Sandbox: Continual Learning and Adaptation for Situated Human-Robot Collaboration. - Jennifer Grannen; Siddharth Karamcheti; Suvir Mirchandani; Percy Liang; Dorsa Sadigh (CoRL, 2024)

ReMix: Optimizing Data Mixtures for Large Scale Imitation Learning. - Joey Hejna; Chethan Anand Bhateja; Yichen Jiang; Karl Pertsch; Dorsa Sadigh (CoRL, 2024)

OpenVLA: An Open-Source Vision-Language-Action Model. - Moo Jin Kim; Karl Pertsch; Siddharth Karamcheti; Ted Xiao; Ashwin Balakrishna; Suraj Nair 003; Rafael Rafailov; Ethan Paul Foster; Pannag R. Sanketi; Quan Vuong; Thomas Kollar; Benjamin Burchfiel; et al. (CoRL, 2024)

FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation Learning. - Li-Heng Lin; Yuchen Cui; Amber Xie; Tianyu Hua; Dorsa Sadigh (CoRL, 2024)

So You Think You Can Scale Up Autonomous Robot Data Collection? - Suvir Mirchandani; Suneel Belkhale; Joey Hejna; Evelyn Choi; Md Sazzad Islam; Dorsa Sadigh (CoRL, 2024)

RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches. - Priya Sundaresan; Quan Vuong; Jiayuan Gu; Peng Xu 010; Ted Xiao; Sean Kirmani; Tianhe Yu; Michael Stark 003; Ajinkya Jain; Karol Hausman; Dorsa Sadigh; Jeannette Bohg; et al. (CoRL, 2024)

SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities. - Boyuan Chen 003; Zhuo Xu; Sean Kirmani; Brian Ichter; Dorsa Sadigh; Leonidas J. Guibas; Fei Xia 002 (CVPR, 2024)

Generative Expressive Robot Behaviors using Large Language Models. - Karthik Mahadevan; Jonathan Chien; Noah Brown; Zhuo Xu; Carolina Parada; Fei Xia 002; Andy Zeng 001; Leila Takayama; Dorsa Sadigh (HRI, 2024)

Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. - Joey Hejna; Rafael Rafailov; Harshit Sikchi; Chelsea Finn; Scott Niekum; W. Bradley Knox; Dorsa Sadigh (ICLR, 2024)

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. - Chengshu Li 002; Jacky Liang; Andy Zeng 001; Xinyun Chen; Karol Hausman; Dorsa Sadigh; Sergey Levine; Li Fei-Fei 001; Fei Xia 002; Brian Ichter (ICML, 2024)

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models. - Siddharth Karamcheti; Suraj Nair 003; Ashwin Balakrishna; Percy Liang; Thomas Kollar; Dorsa Sadigh (ICML, 2024)

How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies. - Montserrat Gonzalez Arenas; Ted Xiao; Sumeet Singh; Vidhi Jain; Allen Z. Ren; Quan Vuong; Jake Varley; Alexander Herzog; Isabel Leal; Sean Kirmani; Mario Prats; Dorsa Sadigh; et al. (ICRA, 2024)

Physically Grounded Vision-Language Models for Robotic Manipulation. - Jensen Gao; Bidipta Sarkar; Fei Xia 002; Ted Xiao; Jiajun Wu 001; Brian Ichter; Anirudha Majumdar; Dorsa Sadigh (ICRA, 2024)

Toward Grounded Commonsense Reasoning. - Minae Kwon; Hengyuan Hu; Vivek Myers; Siddharth Karamcheti; Anca D. Dragan; Dorsa Sadigh (ICRA, 2024)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 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 001; Fei Xia 002; Dorsa Sadigh (ICRA, 2024)

RT-H: Action Hierarchies using Language. - Suneel Belkhale; Tianli Ding; Ted Xiao; Pierre Sermanet; Quan Vuong; Jonathan Tompson; Yevgen Chebotar; Debidatta Dwibedi; Dorsa Sadigh (Robotics: Science and Systems, 2024)

Efficient Data Collection for Robotic Manipulation via Compositional Generalization. - Jensen Gao; Annie Xie; Ted Xiao; Chelsea Finn; Dorsa Sadigh (Robotics: Science and Systems, 2024)

Octo: An Open-Source Generalist Robot Policy. - Dibya Ghosh; Homer Rich Walke; Karl Pertsch; Kevin Black; Oier Mees; Sudeep Dasari; Joey Hejna; Tobias Kreiman; Charles Xu 003; Jianlan Luo; You Liang Tan; Lawrence Yunliang Chen; et al. (Robotics: Science and Systems, 2024)

Imitation Bootstrapped Reinforcement Learning. - Hengyuan Hu; Suvir Mirchandani; Dorsa Sadigh (Robotics: Science and Systems, 2024)

FLAIR: Feeding via Long-Horizon AcquIsition of Realistic dishes. - Rajat Kumar Jenamani; Priya Sundaresan; Maram Sakr; Tapomayukh Bhattacharjee; Dorsa Sadigh (Robotics: Science and Systems, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (Robotics: Science and Systems, 2024)

Learning to Learn Faster from Human Feedback with Language Model Predictive Control. - Jacky Liang; Fei Xia 002; Wenhao Yu 003; Andy Zeng 001; Maria Attarian; Maria Bauzá Villalonga; Matthew Bennice; Alex Bewley; Adil Dostmohamed; Chuyuan Fu; Nimrod Gileadi; Marissa Giustina; et al. (Robotics: Science and Systems, 2024)

Explore until Confident: Efficient Exploration for Embodied Question Answering. - Allen Z. Ren; Jaden Clark; Anushri Dixit; Masha Itkina; Anirudha Majumdar; Dorsa Sadigh (Robotics: Science and Systems, 2024)

Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation. - Jonathan Heewon Yang; Catherine Glossop; Arjun Bhorkar; Dhruv Shah; Quan Vuong; Chelsea Finn; Dorsa Sadigh; Sergey Levine (Robotics: Science and Systems, 2024)

SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities. - Boyuan Chen 003; Zhuo Xu; Sean Kirmani; Brian Ichter; Danny Driess; Pete Florence; Dorsa Sadigh; Leonidas J. Guibas; Fei Xia 002 (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; et al. (CoRR, 2024)

Learning to Learn Faster from Human Feedback with Language Model Predictive Control. - Jacky Liang; Fei Xia 002; Wenhao Yu 003; Andy Zeng 001; Montserrat Gonzalez Arenas; Maria Attarian; Maria Bauzá 001; Matthew Bennice; Alex Bewley; Adil Dostmohamed; Chuyuan Kelly Fu; Nimrod Gileadi; et al. (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)

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)

Policy Learning with a Language Bottleneck. - Megha Srivastava; Cédric Colas; Dorsa Sadigh; Jacob Andreas (CoRR, 2024)

Octo: An Open-Source Generalist Robot Policy. - Octo Model Team; Dibya Ghosh; Homer Walke; Karl Pertsch; Kevin Black; Oier Mees; Sudeep Dasari; Joey Hejna; Tobias Kreiman; Charles Xu 003; Jianlan Luo; You Liang Tan; et al. (CoRR, 2024)

VADER: Visual Affordance Detection and Error Recovery for Multi Robot Human Collaboration. - Michael Ahn; Montserrat Gonzalez Arenas; Matthew Bennice; Noah Brown; Christine Chan; Byron David; Anthony G. Francis; Gavin Gonzalez; Rainer Hessmer; Tomas Jackson; Nikhil J. Joshi; Daniel Lam; et al. (CoRR, 2024)

OpenVLA: An Open-Source Vision-Language-Action Model. - Moo Jin Kim; Karl Pertsch; Siddharth Karamcheti; Ted Xiao; Ashwin Balakrishna; Suraj Nair 003; Rafael Rafailov; Ethan Paul Foster; Grace Lam; Pannag Sanketi; Quan Vuong; Thomas Kollar; et al. (CoRR, 2024)

Re-Mix: Optimizing Data Mixtures for Large Scale Imitation Learning. - Joey Hejna; Chethan Bhateja; Yichen Jiang; Karl Pertsch; Dorsa Sadigh (CoRR, 2024)

Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation. - Homanga Bharadhwaj; Debidatta Dwibedi; Abhinav Gupta 001; Shubham Tulsiani; Carl Doersch; Ted Xiao; Dhruv Shah; Fei Xia 002; Dorsa Sadigh; Sean Kirmani (CoRR, 2024)

RoboCrowd: Scaling Robot Data Collection through Crowdsourcing. - Suvir Mirchandani; David D. Yuan; Kaylee Burns; Md Sazzad Islam; Tony Z. Zhao; Chelsea Finn; Dorsa Sadigh (CoRR, 2024)

RT-Affordance: Affordances are Versatile Intermediate Representations for Robot Manipulation. - Soroush Nasiriany; Sean Kirmani; Tianli Ding; Laura Smith; Yuke Zhu; Danny Driess; Dorsa Sadigh; Ted Xiao (CoRR, 2024)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma; Joey Hejna; Ayzaan Wahid; Chuyuan Fu; Dhruv Shah; Jacky Liang; Zhuo Xu; Sean Kirmani; Peng Xu 010; Danny Driess; Ted Xiao; Jonathan Tompson; et al. (CoRR, 2024)

Active preference-based Gaussian process regression for reward learning and optimization. - Erdem Biyik; Nicolas Huynh; Mykel J. Kochenderfer; Dorsa Sadigh (Int. J. Robotics Res., 2024)

Selected papers from WAFR 2022. - Jason M. O'Kane; Michael W. Otte; Dorsa Sadigh; Pratap Tokekar (Int. J. Robotics Res., 2024)

Batch Active Learning of Reward Functions from Human Preferences. - Erdem Biyik; Nima Anari; Dorsa Sadigh (ACM Trans. Hum. Robot Interact., 2024)

Shared Autonomy for Proximal Teaching. - Megha Srivastava; Reihaneh Iranmanesh; Yuchen Cui; Deepak Edakkattil Gopinath; Emily Sarah Sumner; Andrew Silva; Laporsha Dees; Guy Rosman; Dorsa Sadigh (HRI, 2025)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma; Joey Hejna; Chuyuan Fu; Dhruv Shah; Jacky Liang; Zhuo Xu; Sean Kirmani; Peng Xu 010; Danny Driess; Ted Xiao; Osbert Bastani; Dinesh Jayaraman; et al. (ICLR, 2025)

What's the Move? Hybrid Imitation Learning via Salient Points. - Priya Sundaresan; Hengyuan Hu; Quan Vuong; Jeannette Bohg; Dorsa Sadigh (ICLR, 2025)

Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning. - Bidipta Sarkar; Warren Xia; C. Karen Liu; Dorsa Sadigh (AAMAS, 2025)

Motion Tracks: A Unified Representation for Human-Robot Transfer in Few-Shot Imitation Learning. - Juntao Ren; Priya Sundaresan; Dorsa Sadigh; Sanjiban Choudhury; Jeannette Bohg (CoRR, 2025)

Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning. - Jaden Clark; Joey Hejna; Dorsa Sadigh (CoRR, 2025)

Action-Free Reasoning for Policy Generalization. - Jaden Clark; Suvir Mirchandani; Dorsa Sadigh; Suneel Belkhale (CoRR, 2025)

Robot Data Curation with Mutual Information Estimators. - Joey Hejna; Suvir Mirchandani; Ashwin Balakrishna; Annie Xie; Ayzaan Wahid; Jonathan Tompson; Pannag Sanketi; Dhruv Shah; Coline Devin; Dorsa Sadigh (CoRR, 2025)

Unified Video Action Model. - Shuang Li; Yihuai Gao; Dorsa Sadigh; Shuran Song (CoRR, 2025)

A Taxonomy for Evaluating Generalist Robot Policies. - Jensen Gao; Suneel Belkhale; Sudeep Dasari; Ashwin Balakrishna; Dhruv Shah; Dorsa Sadigh (CoRR, 2025)

How to Train Your Robots? The Impact of Demonstration Modality on Imitation Learning. - Haozhuo Li; Yuchen Cui; Dorsa Sadigh (CoRR, 2025)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 2025)

A Study of Perceived Safety for Soft Robotics in Caregiving Tasks. - Cosima du Pasquier; Jennifer Grannen; Chuer Pan; Serin L. Huber; Aliyah Smith; Monroe Kennedy III; Shuran Song; Dorsa Sadigh; Allison M. Okamura (CoRR, 2025)

MotIF: Motion Instruction Fine-Tuning. - Minyoung Hwang; Joey Hejna; Dorsa Sadigh; Yonatan Bisk (IEEE Robotics Autom. Lett., 2025)

Latent Diffusion Planning for Imitation Learning. - Amber Xie; Oleh Rybkin; Dorsa Sadigh; Chelsea Finn (CoRR, 2025)

Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Autospeculation. - Hengyuan Hu; Aniket Das; Dorsa Sadigh; Nima Anari (CoRR, 2025)

What Matters for Batch Online Reinforcement Learning in Robotics? - Perry Dong; Suvir Mirchandani; Dorsa Sadigh; Chelsea Finn (CoRR, 2025)

HoMeR: Learning In-the-Wild Mobile Manipulation via Hybrid Imitation and Whole-Body Control. - Priya Sundaresan; Rhea Malhotra; Phillip Miao; Jingyun Yang; Jimmy Wu; Hengyuan Hu; Rika Antonova; Francis Engelmann; Dorsa Sadigh; Jeannette Bohg (CoRR, 2025)

Bridging Perception and Action: Spatially-Grounded Mid-Level Representations for Robot Generalization. - Jonathan Yang; Chuyuan Kelly Fu; Dhruv Shah; Dorsa Sadigh; Fei Xia 002; Tingnan Zhang (CoRR, 2025)

Scaffolding Dexterous Manipulation with Vision-Language Models. - Vincent de Bakker; Joey Hejna; Tyler Ga Wei Lum; Onur Celik; Aleksandar Taranovic; Denis Blessing; Gerhard Neumann; Jeannette Bohg; Dorsa Sadigh (CoRR, 2025)

EXPO: Stable Reinforcement Learning with Expressive Policies. - Perry Dong; Qiyang Li; Dorsa Sadigh; Chelsea Finn (CoRR, 2025)

ProVox: Personalization and Proactive Planning for Situated Human-Robot Collaboration. - Jennifer Grannen; Siddharth Karamcheti; Blake Wulfe; Dorsa Sadigh (IEEE Robotics Autom. Lett., 2025)