Dorsa Sadigh

Stanford University

収録論文 141本 ・ フィジカルAI/ロボット学習

※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。

論文

• 世界モデルを用いたQ学習
  強化学習2026/8/17

  Q学習に世界モデルを組み合わせ、実データのみで学習しつつ想像上の軌道で探索を行うことで、サンプル効率と性能を向上させる手法を提案した。

• Cross-Embodiment Transfer via Behavior-Aligned Representations
  2026/7/30
• VIA: Visual Interface Agent for Robot Control
  2026/7/1
• Cross-Embodiment Transfer via Behavior-Aligned Representations
  2026/7/1
• EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models
  2026/5/1
• Proximal State Nudging: Reducing Skill Atrophy from AI Assistance
  2026/5/1
• Will People Enjoy a Robot Trainer? A Case Study with Snoopie the Pacerbot
  2026/4/1
• HandelBot: Real-World Piano Playing via Fast Adaptation of Dexterous Robot Policies
  2026/3/1
• Grounding Robot Generalization in Training Data via Retrieval-Augmented VLMs
  2026/3/1
• Data Analogies Enable Efficient Cross-Embodiment Transfer
  2026/3/1
• DexDrummer: In-Hand, Contact-Rich, and Long-Horizon Dexterous Robot Drumming
  2026/3/1
• SteerVLA: Steering Vision-Language-Action Models in Long-Tail Driving Scenarios
  2026/2/1
• RoboCade: Gamifying Robot Data Collection
  2025/12/1
• Invariance Co-training for Robot Visual Generalization
  2025/12/1
• Robot-Powered Data Flywheels: Deploying Robots in the Wild for Continual Data Collection and Foundation Model Adaptation
  2025/11/1
• Data Retrieval with Importance Weights for Few-Shot Imitation Learning
  2025/9/1
• Scaffolding Dexterous Manipulation with Vision-Language Models
  2025/6/1
• Bridging Perception and Action: Spatially-Grounded Mid-Level Representations for Robot Generalization
  2025/6/1
• HoMeR: Learning In-the-Wild Mobile Manipulation via Hybrid Imitation and Whole-Body Control
  2025/6/1
• ProVox: Personalization and Proactive Planning for Situated Human-Robot Collaboration
  2025/6/1
• What Matters for Batch Online Reinforcement Learning in Robotics?
  2025/5/1
• Latent Diffusion Planning for Imitation Learning
  2025/4/1
• How to Train Your Robots? The Impact of Demonstration Modality on Imitation Learning
  2025/3/1
• A Taxonomy for Evaluating Generalist Robot Manipulation Policies
  2025/3/1
• Unified Video Action Model
  2025/3/1
• A Study of Perceived Safety for Soft Robotics in Caregiving Tasks
  2025/3/1
• Gemini Robotics: Bringing AI into the Physical World
  2025/3/1
• Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning
  2025/2/1
• Action-Free Reasoning for Policy Generalization
  2025/2/1
• Shared Autonomy for Proximal Teaching
  2025/2/1
• Robot Data Curation with Mutual Information Estimators
  2025/2/1
• Motion Tracks: A Unified Representation for Human-Robot Transfer in Few-Shot Imitation Learning
  2025/1/1
• What's the Move? Hybrid Imitation Learning via Salient Points
  2024/12/1
• RoboCrowd: Scaling Robot Data Collection through Crowdsourcing
  2024/11/1
• Vision Language Models are In-Context Value Learners
  2024/11/1
• Vocal Sandbox: Continual Learning and Adaptation for Situated Human-Robot Collaboration
  2024/11/1
• RT-Affordance: Affordances are Versatile Intermediate Representations for Robot Manipulation
  2024/11/1
• So You Think You Can Scale Up Autonomous Robot Data Collection?
  2024/11/1
• MotIF: Motion Instruction Fine-tuning
  2024/9/1
• Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation
  2024/9/1
• Re-Mix: Optimizing Data Mixtures for Large Scale Imitation Learning
  2024/8/1
• FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation Learning
  2024/8/1
• FLAIR: Feeding via Long-horizon AcquIsition of Realistic dishes
  2024/7/1
• OpenVLA: An Open-Source Vision-Language-Action Model
  2024/6/1
• Octo: An Open-Source Generalist Robot Policy
  2024/5/1
• VADER: Visual Affordance Detection and Error Recovery for Multi Robot Human Collaboration
  2024/5/1
• DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
  2024/3/1
• Efficient Data Collection for Robotic Manipulation via Compositional Generalization
  2024/3/1
• Explore until Confident: Efficient Exploration for Embodied Question Answering
  2024/3/1
• RT-H: Action Hierarchies Using Language
  2024/3/1
• RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches
  2024/3/1
• Batch Active Learning of Reward Functions from Human Preferences
  2024/2/1
• Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation
  2024/2/1
• Learning to Learn Faster from Human Feedback with Language Model Predictive Control
  2024/2/1
• Generative Expressive Robot Behaviors using Large Language Models
  2024/1/1
• SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities
  2024/1/1
• AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents
  2024/1/1
• Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
  2023/12/1
• Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections
  2023/11/1
• RoboCLIP: One Demonstration is Enough to Learn Robot Policies
  2023/10/1
• Open X-Embodiment: Robotic Learning Datasets and RT-X Models
  2023/10/1
• Physically Grounded Vision-Language Models for Robotic Manipulation
  2023/9/1
• Gesture-Informed Robot Assistance via Foundation Models
  2023/9/1
• Robots That Can See: Leveraging Human Pose for Trajectory Prediction
  2023/9/1
• Stabilize to Act: Learning to Coordinate for Bimanual Manipulation
  2023/9/1
• Learning Sequential Acquisition Policies for Robot-Assisted Feeding
  2023/9/1
• Large Language Models as General Pattern Machines
  2023/7/1
• Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners
  2023/7/1
• Polybot: Training One Policy Across Robots While Embracing Variability
  2023/7/1
• Toward Grounded Commonsense Reasoning
  2023/6/1
• HYDRA: Hybrid Robot Actions for Imitation Learning
  2023/6/1
• KITE: Keypoint-Conditioned Policies for Semantic Manipulation
  2023/6/1
• Language to Rewards for Robotic Skill Synthesis
  2023/6/1
• Generating Language Corrections for Teaching Physical Control Tasks
  2023/6/1
• Data Quality in Imitation Learning
  2023/6/1
• Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets
  2023/4/1
• Soy: An Efficient MILP Solver for Piecewise-Affine Systems
  2023/3/1
• Active Reward Learning from Online Preferences
  2023/2/1
• Language-Driven Representation Learning for Robotics
  2023/2/1
• "No, to the Right" -- Online Language Corrections for Robotic Manipulation via Shared Autonomy
  2023/1/1
• Few-Shot Preference Learning for Human-in-the-Loop RL
  2022/12/1
• Learning Bimanual Scooping Policies for Food Acquisition
  2022/11/1
• Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding
  2022/11/1
• Assistive Teaching of Motor Control Tasks to Humans
  2022/11/1
• Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation
  2022/11/1
• In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing
  2022/11/1
• Eliciting Compatible Demonstrations for Multi-Human Imitation Learning
  2022/10/1
• Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations
  2022/9/1
• Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction
  2022/3/1
• Weakly Supervised Correspondence Learning
  2022/3/1
• PLATO: Predicting Latent Affordances Through Object-Centric Play
  2022/3/1
• Learning from Imperfect Demonstrations via Adversarial Confidence Transfer
  2022/2/1
• LILA: Language-Informed Latent Actions
  2021/11/1
• Balancing Efficiency and Comfort in Robot-Assisted Bite Transfer
  2021/11/1
• Learning Reward Functions from Scale Feedback
  2021/10/1
• Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality
  2021/10/1
• Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams
  2021/10/1
• Learning Feasibility to Imitate Demonstrators with Different Dynamics
  2021/10/1
• From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
  2021/10/1
• Influencing Towards Stable Multi-Agent Interactions
  2021/10/1
• Learning Multimodal Rewards from Rankings
  2021/9/1
• APReL: A Library for Active Preference-based Reward Learning Algorithms
  2021/8/1
• Cooperative Autonomous Vehicles that Sympathize with Human Drivers
  2021/7/1
• Social Coordination and Altruism in Autonomous Driving
  2021/7/1
• Learning Latent Actions to Control Assistive Robots
  2021/7/1
• Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic
  2021/7/1
• Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy
  2021/6/1
• Learning Visually Guided Latent Actions for Assistive Teleoperation
  2021/5/1
• Learning Human Objectives from Sequences of Physical Corrections
  2021/4/1
• On the Critical Role of Conventions in Adaptive Human-AI Collaboration
  2021/4/1
• ELLA: Exploration through Learned Language Abstraction
  2021/3/1
• Learning from Imperfect Demonstrations from Agents with Varying Dynamics
  2021/3/1
• Transfer Reinforcement Learning across Homotopy Classes
  2021/2/1
• ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes
  2020/11/1
• Learning Latent Representations to Influence Multi-Agent Interaction
  2020/11/1
• Learning Adaptive Language Interfaces through Decomposition
  2020/10/1
• Multi-Agent Safe Planning with Gaussian Processes
  2020/8/1
• Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving
  2020/7/1
• Learning User-Preferred Mappings for Intuitive Robot Control
  2020/7/1
• Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences
  2020/6/1
• Formalizing and Guaranteeing* Human-Robot Interaction
  2020/6/1
• Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints
  2020/5/1
• Active Preference-Based Gaussian Process Regression for Reward Learning
  2020/5/1
• Shared Autonomy with Learned Latent Actions
  2020/5/1
• When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans
  2020/1/1
• Learning from My Partner's Actions: Roles in Decentralized Robot Teams
  2019/10/1
• Asking Easy Questions: A User-Friendly Approach to Active Reward Learning
  2019/10/1
• Robots that Take Advantage of Human Trust
  2019/9/1
• Learning How to Dynamically Route Autonomous Vehicles on Shared Roads
  2019/9/1
• Controlling Assistive Robots with Learned Latent Actions
  2019/9/1
• Learning Reward Functions by Integrating Human Demonstrations and Preferences
  2019/6/1
• Deep Local Trajectory Replanning and Control for Robot Navigation
  2019/5/1
• The Green Choice: Learning and Influencing Human Decisions on Shared Roads
  2019/4/1
• Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models
  2019/4/1
• Unsupervised Visuomotor Control through Distributional Planning Networks
  2019/2/1
• Altruistic Autonomy: Beating Congestion on Shared Roads
  2018/10/1
• Efficient and Trustworthy Social Navigation Via Explicit and Implicit Robot-Human Communication
  2018/10/1
• Hierarchical Game-Theoretic Planning for Autonomous Vehicles
  2018/10/1
• Batch Active Preference-Based Learning of Reward Functions
  2018/10/1
• Maximizing Road Capacity Using Cars that Influence People
  2018/7/1
• Safe Control under Uncertainty
  2015/10/1