{"total":82,"rows":[{"id":"2602.15922","title":"World Action Models are Zero-shot Policies","created":"2026-02-17","cited_by_count":465,"area":"wm"},{"id":"2604.26694","title":"Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising","created":"2026-04-29","cited_by_count":71,"area":"wm"},{"id":"2605.12090","title":"World Action Models: The Next Frontier in Embodied AI","created":"2026-05-12","cited_by_count":50,"area":"wm"},{"id":"2607.05391","title":"LLM-as-a-Verifier: A General-Purpose Verification Framework","created":"2026-07-06","cited_by_count":30,"area":"lr"},{"id":"2605.15195","title":"VGGT-$\\Omega$","created":"2026-05-14","cited_by_count":26,"area":null},{"id":"2601.07060","title":"PALM: Progress-Aware Policy Learning via Affordance Reasoning for Long-Horizon Robotic Manipulation","created":"2026-01-11","cited_by_count":21,"area":"vla"},{"id":"2607.08436","title":"EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Data","created":"2026-07-08","cited_by_count":20,"area":"wm"},{"id":"2604.01985","title":"World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry","created":"2026-04-02","cited_by_count":18,"area":"wm"},{"id":"2604.22748","title":"Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond","created":"2026-04-24","cited_by_count":14,"area":"wm"},{"id":"2603.02573","title":"Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels","created":"2026-03-03","cited_by_count":13,"area":null},{"id":"2603.13215","title":"Out of Sight, Out of Mind? Evaluating State Evolution in Video World Models","created":"2026-03-13","cited_by_count":13,"area":"wm"},{"id":"2608.08023","title":"4D-WAM: Infusing Spatiotemporal Awareness into World Action Models through Trajectory Fields","created":"2026-08-08","cited_by_count":13,"area":"wm"},{"id":"2603.16669","title":"Kinema4D: Kinematic 4D World Modeling for Spatiotemporal Embodied Simulation","created":"2026-03-17","cited_by_count":12,"area":"wm"},{"id":"2606.20781","title":"World Action Models: A Survey","created":"2026-06-18","cited_by_count":12,"area":"wm"},{"id":"2602.09013","title":"Dexterous Manipulation Policies from RGB Human Videos via 3D Hand-Object Trajectory Reconstruction","created":"2026-02-09","cited_by_count":11,"area":null},{"id":"2606.17046","title":"Geometric Action Model for Robot Policy Learning","created":"2026-06-15","cited_by_count":11,"area":"wm"},{"id":"2608.10860","title":"Flex-$\\pi$: A Multi-Stream World-Action Model with Compute Flexibility","created":"2026-08-11","cited_by_count":11,"area":"wm"},{"id":"2605.12369","title":"GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization","created":"2026-05-12","cited_by_count":10,"area":"mllm"},{"id":"2607.19343","title":"Masked Visual Actions for Unified World Modeling","created":"2026-07-21","cited_by_count":9,"area":"wm"},{"id":"2603.01549","title":"Pri4R: Learning World Dynamics for Vision-Language-Action Models with Privileged 4D Representation","created":"2026-03-02","cited_by_count":8,"area":"vla"},{"id":"2604.23001","title":"Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines","created":"2026-04-24","cited_by_count":8,"area":"vla"},{"id":"2605.22882","title":"GEM-4D: Geometry-Enhanced Video World Models for Robot Manipulation","created":"2026-05-20","cited_by_count":8,"area":"wm"},{"id":"2607.19190","title":"Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents","created":"2026-07-21","cited_by_count":8,"area":"wm"},{"id":"2608.04996","title":"DreamWAM: Beyond RGB Future Prediction for World Action Models","created":"2026-08-05","cited_by_count":8,"area":"wm"},{"id":"2605.23856","title":"Point Tracking Improves World Action Models","created":"2026-05-22","cited_by_count":7,"area":"wm"},{"id":"2605.19242","title":"PhyWorld: Physics-Faithful World Model for Video Generation","created":"2026-05-19","cited_by_count":6,"area":"wm"},{"id":"2609.16074","title":"World-Action Models for Robot Learning and Control: A Survey","created":"2026-09-13","cited_by_count":6,"area":"wm"},{"id":"2604.16592","title":"Human Cognition in Machines: A Unified Perspective of World Models","created":"2026-04-17","cited_by_count":5,"area":"wm"},{"id":"2605.12587","title":"TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking","created":"2026-05-12","cited_by_count":5,"area":"diffusion"},{"id":"2605.17522","title":"RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation","created":"2026-05-17","cited_by_count":5,"area":"wm"},{"id":"2605.23993","title":"Nano World Models: A Minimalist Implementation of Future Video Prediction","created":"2026-05-17","cited_by_count":5,"area":"wm"},{"id":"2606.11628","title":"LUCID: Learning Embodiment-Agnostic Intent Models from Unstructured Human Videos for Scalable Dexterous Robot Skill Acquisition","created":"2026-06-10","cited_by_count":5,"area":null},{"id":"2606.18558","title":"MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction","created":"2026-06-17","cited_by_count":5,"area":null},{"id":"2602.02402","title":"SoMA: A Real-to-Sim Neural Simulator for Robotic Soft-body Manipulation","created":"2026-02-02","cited_by_count":4,"area":null},{"id":"2605.07079","title":"Learning Visual Feature-Based World Models via Residual Latent Action","created":"2026-05-08","cited_by_count":4,"area":"wm"},{"id":"2605.09196","title":"RigidFormer: Learning Rigid Dynamics using Transformers","created":"2026-05-09","cited_by_count":3,"area":null},{"id":"2606.00133","title":"World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications","created":"2026-05-28","cited_by_count":3,"area":"wm"},{"id":"2606.13769","title":"$\\mu_0$: A Scalable 3D Interaction-Trace World Model","created":"2026-06-11","cited_by_count":3,"area":"wm"},{"id":"2604.09411","title":"SynFlow: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data","created":"2026-04-10","cited_by_count":2,"area":null},{"id":"2606.06556","title":"Robots Need More than VLA and World Models","created":"2026-06-04","cited_by_count":2,"area":"wm"},{"id":"2606.32028","title":"DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation","created":"2026-06-30","cited_by_count":2,"area":"wm"},{"id":"2607.13451","title":"Learning Physics-Guided Residual Dynamics for Deformable Object Simulation","created":"2026-07-15","cited_by_count":2,"area":null},{"id":"2607.22000","title":"Music-JEPA: Learning a World Model of Sound from Action","created":"2026-07-24","cited_by_count":2,"area":"wm"},{"id":"2608.24101","title":"TrAct: Bridging Robot Control and Visual Prediction with Visual Tracks","created":"2026-08-25","cited_by_count":2,"area":"wm"},{"id":"2608.25956","title":"4DGS-WAM: Bridging Past and Future with an Object-Centric World Action Model based on 4D Gaussian Splatting","created":"2026-08-26","cited_by_count":2,"area":"wm"},{"id":"2609.19142","title":"PointZero: 3D Point Track Completion for Learning Transferable 3D Dynamics","created":"2026-09-16","cited_by_count":2,"area":"wm"},{"id":"2602.00785","title":"World Models as an Intermediary between Agents and the Real World","created":"2026-01-31","cited_by_count":1,"area":"wm"},{"id":"2605.01799","title":"Embody4D: A Generalist Data Engine for Embodied 4D World Modeling","created":"2026-05-03","cited_by_count":1,"area":"wm"},{"id":"2606.15015","title":"NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics","created":"2026-06-12","cited_by_count":1,"area":null},{"id":"2607.00148","title":"3D Point World Models: Point Completion Enables More Accurate Dynamics Learning","created":"2026-06-30","cited_by_count":1,"area":"wm"},{"id":"2607.16192","title":"MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction","created":"2026-07-17","cited_by_count":1,"area":null},{"id":"2607.20653","title":"PhysCoRe: Physics-Corrected Residual World Models for Material-Aware Deformable Dynamics","created":"2026-07-22","cited_by_count":1,"area":"wm"},{"id":"2607.23517","title":"Real-Time Human-Centric World Modeling for Upper-Body Human-Object Interaction","created":"2026-07-26","cited_by_count":1,"area":"wm"},{"id":"2603.26690","title":"SpatialPoint: Spatial-aware Point Prediction for Embodied Localization","created":"2026-03-16","cited_by_count":0,"area":null},{"id":"2604.08475","title":"LAMP: Lift Image-Editing as General 3D Priors for Open-world Manipulation","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2605.20737","title":"Resolving Long-Tail Ambiguity in Unsupervised 3D Point Cloud Segmentation with Language Priors","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2605.24630","title":"DexSIM: Real-time Dexterous Simulation with Unified Causal Video Diffusion","created":"2026-05-23","cited_by_count":0,"area":"diffusion"},{"id":"2606.12189","title":"DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2606.14585","title":"Sensitivity Shaping for Latent Modeling","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2607.05390","title":"Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models","created":"2026-07-06","cited_by_count":0,"area":"wm"},{"id":"2608.02713","title":"Quo Vadis, World Modeling?","created":"2026-08-03","cited_by_count":0,"area":"wm"},{"id":"2608.23070","title":"From Generation to Simulation: How Far Are World Models from Being True Simulators?","created":"2026-08-24","cited_by_count":0,"area":"wm"},{"id":"2609.03927","title":"Toward Unified Robot Learning: Bridging Representation, Vision-Language-Action, and World Models","created":"2026-09-03","cited_by_count":0,"area":"wm"},{"id":"2609.06837","title":"BinauralVAE: Spatial Audio Reconstruction For World Models","created":"2026-09-06","cited_by_count":0,"area":"wm"},{"id":"2609.08855","title":"Earth System World Model for What-If Simulations: A Case Study for Terrestrial Ecosystems","created":"2026-09-08","cited_by_count":0,"area":"wm"},{"id":"2609.19119","title":"Track, Articulate, Act: Generating Articulation from Casual Human Videos","created":"2026-09-16","cited_by_count":0,"area":null},{"id":"2609.25322","title":"JAMB: Joint Action-Motion Diffusion for Bimanual Manipulation","created":"2026-09-21","cited_by_count":0,"area":"diffusion"},{"id":"2609.28393","title":"PointCast: One World Model for Rigid, Articulated, and Deformable Object Manipulation","created":"2026-09-23","cited_by_count":0,"area":"wm"},{"id":"2609.34414","title":"From World Models to World Action Models: Rethinking Next-State Prediction","created":"2026-09-28","cited_by_count":0,"area":"wm"},{"id":"2610.00981","title":"NarrativeFlow: Flow-Based Vision-Language-Action Model Using Robot Velocity Fields","created":"2026-10-01","cited_by_count":0,"area":"vla"},{"id":"2610.01744","title":"3DROID: A Renderable 3D Gaussian Dataset with Measured Per-Scene Reliability","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.02840","title":"PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation","created":"2026-10-02","cited_by_count":0,"area":"wm"},{"id":"2610.04607","title":"ForeAct3D: Policy-Grounded Future World Modeling for VLA Policies","created":"2026-10-03","cited_by_count":0,"area":"wm"},{"id":"2610.06598","title":"SimForcing: Distilling Simulation Motion Priors into Real-Domain Robot World Models","created":"2026-10-05","cited_by_count":0,"area":"wm"},{"id":"2610.07031","title":"Artemis: Geometry-Grounded Multi-Agent Driving World Models with Shared 3D State and Progressive Memory Update","created":"2026-10-04","cited_by_count":0,"area":"wm"},{"id":"2610.08780","title":"DepthWorld: 3D World Model for Robot Manipulation","created":"2026-10-06","cited_by_count":0,"area":"wm"},{"id":"2610.10515","title":"RoboJEPA: Scaling Robotic Latent World Models","created":"2026-10-07","cited_by_count":0,"area":"wm"},{"id":"2610.12451","title":"VersaCamVLA: Camera-Configurable VLA Policies for Robotic Manipulation","created":"2026-10-08","cited_by_count":0,"area":"vla"},{"id":"2610.12468","title":"DreamTrue: Action-Faithful Robot World Model with Counterfactual Post-Training","created":"2026-10-08","cited_by_count":0,"area":"wm"},{"id":"2610.13522","title":"Beyond Successful Robot Demonstrations: Learning from Human Interactions and Modeling Failure Dynamics","created":"2026-10-09","cited_by_count":0,"area":"wm"},{"id":"2610.14698","title":"PURE: Refining Feed-forward 3D Reconstruction with Unlabeled Post-training","created":"2026-10-10","cited_by_count":0,"area":null},{"id":"2610.17208","title":"DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}