{"total":56,"rows":[{"id":"2602.15922","title":"World Action Models are Zero-shot Policies","created":"2026-02-17","cited_by_count":465,"area":"wm"},{"id":"2512.13030","title":"Motus: A Unified Latent Action World Model","created":"2025-12-15","cited_by_count":251,"area":"wm"},{"id":"2603.17240","title":"GigaWorld-Policy: An Efficient Action-Centered World--Action Model","created":"2026-03-18","cited_by_count":139,"area":"wm"},{"id":"2602.06949","title":"DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos","created":"2026-02-06","cited_by_count":135,"area":"wm"},{"id":"2604.05014","title":"StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing","created":"2026-04-06","cited_by_count":112,"area":"wm"},{"id":"2605.00078","title":"Being-H0.7: A Latent World-Action Model from Egocentric Videos","created":"2026-04-30","cited_by_count":75,"area":"wm"},{"id":"2509.12201","title":"OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling","created":"2025-09-15","cited_by_count":62,"area":"wm"},{"id":"2606.15768","title":"LaWAM: Latent World Action Models for Efficient Dynamics-Aware Robot Policies","created":"2026-06-14","cited_by_count":52,"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":"2601.05230","title":"Learning Latent Action World Models In The Wild","created":"2026-01-08","cited_by_count":47,"area":"wm"},{"id":"2510.19430","title":"GigaBrain-0: A World Model-Powered Vision-Language-Action Model","created":"2025-10-22","cited_by_count":44,"area":"wm"},{"id":"2510.27607","title":"Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model","created":"2025-10-31","cited_by_count":36,"area":"wm"},{"id":"2512.13644","title":"World Models for Learning Dexterous Hand-Object Interactions from Human Videos","created":"2025-12-15","cited_by_count":31,"area":"wm"},{"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":"2603.29844","title":"DIAL: Decoupling Intent and Action via Latent World Modeling for End-to-End VLA","created":"2026-03-31","cited_by_count":19,"area":"wm"},{"id":"2512.17907","title":"Dexterous World Models","created":"2025-12-19","cited_by_count":18,"area":"wm"},{"id":"2607.13017","title":"FlowWAM: Optical Flow as a Unified Action Representation for World Action Models","created":"2026-07-14","cited_by_count":16,"area":"wm"},{"id":"2603.22281","title":"ThinkJEPA: Empowering Latent World Models with Large Vision-Language Reasoning Model","created":"2026-03-23","cited_by_count":13,"area":"wm"},{"id":"2606.20781","title":"World Action Models: A Survey","created":"2026-06-18","cited_by_count":12,"area":"wm"},{"id":"2606.12217","title":"Making Foresight Actionable: Repurposing Representation Alignment in World Action Models","created":"2026-06-10","cited_by_count":11,"area":"wm"},{"id":"2604.19734","title":"UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling","created":"2026-04-21","cited_by_count":10,"area":"wm"},{"id":"2604.26848","title":"STARRY: Spatial-Temporal Action-Centric World Modeling for Robotic Manipulation","created":"2026-04-29","cited_by_count":10,"area":"wm"},{"id":"2606.09215","title":"MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation","created":"2026-06-08","cited_by_count":10,"area":"wm"},{"id":"2607.06988","title":"WAM-TTT: Steering World-Action Models by Watching Human Play at Test Time","created":"2026-07-08","cited_by_count":8,"area":"wm"},{"id":"2607.14183","title":"Open-AoE: An Open Egocentric Manipulation Dataset and Toolchain for Embodied Learning","created":"2026-07-15","cited_by_count":8,"area":"wm"},{"id":"2606.04463","title":"OSCAR: Omni-Embodiment Action-Conditioned World Model for Robotics","created":"2026-06-03","cited_by_count":7,"area":"wm"},{"id":"2606.21088","title":"MV-WAM: Manifold-Aware World Action Model with Value Augmentation","created":"2026-06-19","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":"2607.03964","title":"Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control","created":"2026-07-04","cited_by_count":5,"area":"wm"},{"id":"2603.11755","title":"Controllable Egocentric Video Generation via Occlusion-Aware Sparse 3D Hand Joints","created":"2026-03-12","cited_by_count":4,"area":"wm"},{"id":"2608.13049","title":"H2R-Bench: Benchmarking Human-to-Robot Manipulation Video Generation in World Models","created":"2026-08-13","cited_by_count":4,"area":"wm"},{"id":"2608.27033","title":"Riemann-1.0: An Embodied World Action Model for Physical AI","created":"2026-08-27","cited_by_count":4,"area":"wm"},{"id":"2603.22286","title":"WorldCache: Content-Aware Caching for Accelerated Video World Models","created":"2026-03-23","cited_by_count":3,"area":"wm"},{"id":"2607.06558","title":"RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation","created":"2026-07-07","cited_by_count":3,"area":"wm"},{"id":"2607.09185","title":"Causally Debiased Latent Action Model for Embodied Action Conditioned World Models","created":"2026-07-10","cited_by_count":3,"area":"wm"},{"id":"2608.22403","title":"LD4WAM: Learning Latent Dynamics from Human Videos for World Action Models","created":"2026-08-23","cited_by_count":3,"area":"wm"},{"id":"2604.26182","title":"Lifting Embodied World Models for Planning and Control","created":"2026-04-28","cited_by_count":2,"area":"wm"},{"id":"2607.28243","title":"EgoGenesis: Egocentric World-Action Modeling with Online Anchored Projective Memory and Action-3D RoPE","created":"2026-07-30","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":"2606.05699","title":"DexFuture: Hierarchical Future-State Visuomotor Targeting for Bimanual Dexterous Tool Use","created":"2026-06-04","cited_by_count":1,"area":"wm"},{"id":"2606.27325","title":"Not All Actions Are Equal: Rethinking Conditioning for Dexterous World Model","created":"2026-06-25","cited_by_count":1,"area":"wm"},{"id":"2607.02865","title":"DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning","created":"2026-07-03","cited_by_count":1,"area":"wm"},{"id":"2608.05706","title":"LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models","created":"2026-08-06","cited_by_count":1,"area":"wm"},{"id":"2608.27406","title":"CLAP: Cross-Embodiment Video World Models are Zero-Shot Physical Simulators","created":"2026-08-27","cited_by_count":1,"area":"wm"},{"id":"2609.00161","title":"IMPACT: Attention Is the Interaction Map for Scalable Interaction-Aware World Model Training","created":"2026-08-31","cited_by_count":1,"area":"wm"},{"id":"2609.31394","title":"InternW0-$Δ$: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data","created":"2026-09-25","cited_by_count":1,"area":"wm"},{"id":"2606.03868","title":"Unified Video-Action Joint Denoising for Dexterous Action and Data Generation","created":"2026-06-02","cited_by_count":0,"area":"wm"},{"id":"2609.26118","title":"GDLAM: Group-Disentangled Latent Action Model for Highly Disentangled Embodied Pretraining","created":"2026-08-10","cited_by_count":0,"area":"wm"},{"id":"2610.02840","title":"PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation","created":"2026-10-02","cited_by_count":0,"area":"wm"},{"id":"2610.03391","title":"Native Action-Prior Learning from Videos for World Action Models","created":"2026-10-02","cited_by_count":0,"area":"wm"},{"id":"2610.07355","title":"Tracking Is Not Permanence: What Video World Models Keep of a Hidden Object","created":"2026-10-05","cited_by_count":0,"area":"wm"},{"id":"2610.10270","title":"Video Prediction Policy 2: Predict Better, Act Better","created":"2026-10-07","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":"2610.14351","title":"Learning Transferable World-Action Models from Task-Paired Human Videos","created":"2026-10-09","cited_by_count":0,"area":"wm"},{"id":"2610.18447","title":"Thinker-WM: A Unified World Model with Shared Multimodal Representations for Embodied Intelligence","created":"2026-10-13","cited_by_count":0,"area":"wm"},{"id":"2610.20160","title":"OneLA: Learning Many Worlds from Latent Actions","created":"2026-10-14","cited_by_count":0,"area":"wm"}],"next_cursor":null}