{"total":57,"rows":[{"id":"2405.17398","title":"Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability","created":"2024-05-27","cited_by_count":347,"area":"wm"},{"id":"2403.03954","title":"3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations","created":"2024-03-06","cited_by_count":116,"area":"diffusion"},{"id":"2605.12090","title":"World Action Models: The Next Frontier in Embodied AI","created":"2026-05-12","cited_by_count":50,"area":"wm"},{"id":"2504.08438","title":"Diffusion Models for Robotic Manipulation: A Survey","created":"2025-04-11","cited_by_count":41,"area":"diffusion"},{"id":"2404.19664","title":"Towards Generalist Robot Learning from Internet Video: A Survey","created":"2024-04-30","cited_by_count":40,"area":null},{"id":"2409.14411","title":"Scaling Diffusion Policy in Transformer to 1 Billion Parameters for Robotic Manipulation","created":"2024-09-22","cited_by_count":38,"area":"diffusion"},{"id":"2402.14407","title":"Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training","created":"2024-02-22","cited_by_count":26,"area":"wm"},{"id":"2411.07223","title":"Grounding Video Models to Actions through Goal Conditioned Exploration","created":"2024-11-11","cited_by_count":26,"area":null},{"id":"2512.24766","title":"Dream2Flow: Bridging Video Generation and Open-World Manipulation with 3D Object Flow","created":"2025-12-31","cited_by_count":25,"area":null},{"id":"2410.22325","title":"Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets","created":"2024-10-29","cited_by_count":23,"area":null},{"id":"2409.18707","title":"Discrete Policy: Learning Disentangled Action Space for Multi-Task Robotic Manipulation","created":"2024-09-27","cited_by_count":19,"area":"diffusion"},{"id":"2510.20813","title":"GSWorld: Closed-Loop Photo-Realistic Simulation Suite for Robotic Manipulation","created":"2025-10-23","cited_by_count":19,"area":null},{"id":"2506.14198","title":"AMPLIFY: Actionless Motion Priors for Robot Learning from Videos","created":"2025-06-17","cited_by_count":18,"area":"wm"},{"id":"2502.01719","title":"MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation","created":"2025-02-03","cited_by_count":16,"area":"moe"},{"id":"2603.21872","title":"Manifold-Aware Exploration for Reinforcement Learning in Video Generation","created":"2026-03-23","cited_by_count":15,"area":"lr"},{"id":"2410.05429","title":"Diffusion Imitation from Observation","created":"2024-10-07","cited_by_count":13,"area":"diffusion"},{"id":"2411.17764","title":"PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement","created":"2024-11-26","cited_by_count":13,"area":"deeprl"},{"id":"2504.15369","title":"Solving New Tasks by Adapting Internet Video Knowledge","created":"2025-04-21","cited_by_count":13,"area":null},{"id":"2601.07823","title":"Robotic Video World Models: A Survey of Applications, Research Challenges, Future Directions","created":"2026-01-12","cited_by_count":13,"area":"wm"},{"id":"2602.10503","title":"Towards Long-Lived Robots: Continual Learning VLA Models via Reinforcement Fine-Tuning","created":"2026-02-11","cited_by_count":13,"area":"vla"},{"id":"2502.20630","title":"Subtask-Aware Visual Reward Learning from Segmented Demonstrations","created":"2025-02-28","cited_by_count":10,"area":"deeprl"},{"id":"2402.17910","title":"Box It to Bind It: Unified Layout Control and Attribute Binding in T2I Diffusion Models","created":"2024-02-27","cited_by_count":9,"area":"diffusion"},{"id":"2410.05255","title":"Bridging SFT and DPO for Diffusion Model Alignment with Self-Sampling Preference Optimization","created":"2024-10-07","cited_by_count":9,"area":"diffusion"},{"id":"2503.23271","title":"Learning Coordinated Bimanual Manipulation Policies using State Diffusion and Inverse Dynamics Models","created":"2025-03-30","cited_by_count":9,"area":null},{"id":"2508.11049","title":"GenFlowRL: Shaping Rewards with Generative Object-Centric Flow in Visual Reinforcement Learning","created":"2025-08-14","cited_by_count":9,"area":"deeprl"},{"id":"2601.05848","title":"Goal Force: Teaching Video Models To Accomplish Physics-Conditioned Goals","created":"2026-01-09","cited_by_count":9,"area":"wm"},{"id":"2407.01903","title":"Text-Aware Diffusion for Policy Learning","created":"2024-07-02","cited_by_count":8,"area":"deeprl"},{"id":"2505.19769","title":"TeViR: Text-to-Video Reward with Diffusion Models for Efficient Reinforcement Learning","created":"2025-05-26","cited_by_count":8,"area":"diffusion"},{"id":"2508.17230","title":"4D Visual Pre-training for Robot Learning","created":"2025-08-24","cited_by_count":8,"area":"diffusion"},{"id":"2506.06658","title":"Self-Improving Loops for Visual Robotic Planning","created":"2025-06-07","cited_by_count":7,"area":null},{"id":"2603.10158","title":"Cross-Hand Latent Representation for Vision-Language-Action Models","created":"2026-03-10","cited_by_count":7,"area":"vla"},{"id":"2410.16411","title":"The Duality of Generative AI and Reinforcement Learning in Robotics: A Review","created":"2024-10-21","cited_by_count":6,"area":"deeprl"},{"id":"2509.26627","title":"TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance","created":"2025-09-30","cited_by_count":6,"area":"deeprl"},{"id":"2605.15855","title":"Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models?","created":"2026-05-15","cited_by_count":6,"area":"diffusion"},{"id":"2512.21586","title":"Videos are Sample-Efficient Supervisions: Behavior Cloning from Videos via Latent Representations","created":"2025-12-25","cited_by_count":5,"area":null},{"id":"2412.10778","title":"Sample-efficient Unsupervised Policy Cloning from Ensemble Self-supervised Labeled Videos","created":"2024-12-14","cited_by_count":4,"area":null},{"id":"2503.09871","title":"LuciBot: Automated Robot Policy Learning from Generated Videos","created":"2025-03-12","cited_by_count":4,"area":null},{"id":"2507.23391","title":"Policy Learning from Large Vision-Language Model Feedback without Reward Modeling","created":"2025-07-31","cited_by_count":4,"area":"mllm"},{"id":"2502.17863","title":"A Survey: Spatiotemporal Consistency in Video Generation","created":"2025-02-25","cited_by_count":3,"area":null},{"id":"2507.05674","title":"Integrating Diffusion-based Multi-task Learning with Online Reinforcement Learning for Robust Quadruped Robot Control","created":"2025-07-08","cited_by_count":3,"area":"diffusion"},{"id":"2512.00961","title":"Goal-Driven Reward by Video Diffusion Models for Reinforcement Learning","created":"2025-11-30","cited_by_count":3,"area":"diffusion"},{"id":"2603.21017","title":"Dreaming the Unseen: World Model-regularized Diffusion Policy for Out-of-Distribution Robustness","created":"2026-03-22","cited_by_count":3,"area":"wm"},{"id":"2606.22027","title":"RARM: Confidence-Gated Progress Reward Modeling for RL in Manipulation","created":"2026-06-20","cited_by_count":3,"area":"alignment"},{"id":"2406.04814","title":"Lifelong Learning of Video Diffusion Models From a Single Video Stream","created":"2024-06-07","cited_by_count":2,"area":"diffusion"},{"id":"2503.14545","title":"PANDORA: Diffusion Policy Learning for Dexterous Robotic Piano Playing","created":"2025-03-17","cited_by_count":2,"area":"diffusion"},{"id":"2505.12583","title":"A Comprehensive Survey on Physical Risk Control in the Era of Foundation Model-enabled Robotics","created":"2025-05-19","cited_by_count":2,"area":null},{"id":"2602.12636","title":"Dual-Granularity Contrastive Reward via Generated Episodic Guidance for Efficient Embodied RL","created":"2026-02-13","cited_by_count":2,"area":"deeprl"},{"id":"2509.22402","title":"ReLAM: Learning Anticipation Model for Rewarding Visual Robotic Manipulation","created":"2025-09-26","cited_by_count":1,"area":"deeprl"},{"id":"2603.01694","title":"MVR: Multi-view Video Reward Shaping for Reinforcement Learning","created":"2026-03-02","cited_by_count":1,"area":"deeprl"},{"id":"2605.08804","title":"Constraint-Aware Diffusion Priors for High-Fidelity and Versatile Quadruped Locomotion","created":"2026-05-09","cited_by_count":1,"area":"diffusion"},{"id":"2607.12892","title":"UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies","created":"2026-07-14","cited_by_count":1,"area":null},{"id":"2601.00452","title":"Imitation from Observations with Trajectory-Level Generative Embeddings","created":"2026-01-01","cited_by_count":0,"area":"offlinerl"},{"id":"2606.03201","title":"Reinforcement Learning from Cross-domain Videos with Video Prediction Model","created":"2026-06-02","cited_by_count":0,"area":"deeprl"},{"id":"2609.09250","title":"No Free Checker: A Survey of Verifiers for Robot Policies","created":"2026-09-08","cited_by_count":0,"area":null},{"id":"2609.36684","title":"ProgressCompass: Embodied Progress Reward Models Are Lost Without the Right Context","created":"2026-09-29","cited_by_count":0,"area":"alignment"},{"id":"2609.38955","title":"Loop-Free Inverse Reinforcement Learning via Sequential Value Recovery with Q-Score Matching","created":"2026-09-30","cited_by_count":0,"area":"diffusion"},{"id":"2610.14159","title":"Disentangling Task-Relevant Latent Dynamics for Reward Modeling","created":"2026-10-09","cited_by_count":0,"area":"alignment"}],"next_cursor":null}