{"total":192,"rows":[{"id":"2506.09985","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","created":"2025-06-11","cited_by_count":809,"area":"wm"},{"id":"2602.15922","title":"World Action Models are Zero-shot Policies","created":"2026-02-17","cited_by_count":465,"area":"wm"},{"id":"2603.16666","title":"Fast-WAM: Do World Action Models Need Test-time Future Imagination?","created":"2026-03-17","cited_by_count":349,"area":"wm"},{"id":"2601.21998","title":"Causal World Modeling for Robot Control","created":"2026-01-29","cited_by_count":321,"area":"wm"},{"id":"2512.13030","title":"Motus: A Unified Latent Action World Model","created":"2025-12-15","cited_by_count":251,"area":"wm"},{"id":"2505.12705","title":"DreamGen: Unlocking Generalization in Robot Learning through Video World Models","created":"2025-05-19","cited_by_count":179,"area":"wm"},{"id":"2606.02800","title":"Cosmos 3: Omnimodal World Models for Physical AI","created":"2026-06-01","cited_by_count":165,"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":"2602.10098","title":"VLA-JEPA: Enhancing Vision-Language-Action Model with Latent World Model","created":"2026-02-10","cited_by_count":118,"area":"wm"},{"id":"2505.15659","title":"FLARE: Robot Learning with Implicit World Modeling","created":"2025-05-21","cited_by_count":113,"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":"2511.17502","title":"RynnVLA-002: A Unified Vision-Language-Action and World Model","created":"2025-11-21","cited_by_count":74,"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":"2510.00406","title":"VLA-RFT: Vision-Language-Action Reinforcement Fine-tuning with Verified Rewards in World Simulators","created":"2025-10-01","cited_by_count":67,"area":"wm"},{"id":"2507.23682","title":"villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models","created":"2025-07-31","cited_by_count":63,"area":"wm"},{"id":"2506.22355","title":"Embodied AI Agents: Modeling the World","created":"2025-06-27","cited_by_count":61,"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":"2507.00917","title":"A Survey: Learning Embodied Intelligence from Physical Simulators and World Models","created":"2025-07-01","cited_by_count":51,"area":"wm"},{"id":"2504.02918","title":"Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems","created":"2025-04-03","cited_by_count":48,"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":"2602.11075","title":"RISE: Self-Improving Robot Policy with Compositional World Model","created":"2026-02-11","cited_by_count":40,"area":"wm"},{"id":"2606.19531","title":"ImageWAM: Do World Action Models Really Need Video Generation, or Just Image Editing?","created":"2026-06-17","cited_by_count":38,"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":"2603.08546","title":"Interactive World Simulator for Robot Policy Training and Evaluation","created":"2026-03-09","cited_by_count":31,"area":"wm"},{"id":"2607.00678","title":"ABot-M0.5: Unified Mobility-and-Manipulation World Action Model","created":"2026-07-01","cited_by_count":30,"area":"wm"},{"id":"2511.14659","title":"NORA-1.5: A Vision-Language-Action Model Trained using World Model- and Action-based Preference Rewards","created":"2025-11-18","cited_by_count":26,"area":"wm"},{"id":"2602.12099","title":"GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning","created":"2026-02-12","cited_by_count":24,"area":"wm"},{"id":"2606.08242","title":"Light-WAM: Efficient World Action Models with State-Fusion Action Decoding","created":"2026-06-06","cited_by_count":23,"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":"2604.19092","title":"RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation","created":"2026-04-21","cited_by_count":19,"area":"wm"},{"id":"2606.05254","title":"Flash-WAM: Modality-Aware Distillation for World Action Models","created":"2026-06-03","cited_by_count":19,"area":"wm"},{"id":"2506.14198","title":"AMPLIFY: Actionless Motion Priors for Robot Learning from Videos","created":"2025-06-17","cited_by_count":18,"area":"wm"},{"id":"2606.11187","title":"Next Forcing: Causal World Modeling with Multi-Chunk Prediction","created":"2026-06-09","cited_by_count":18,"area":"wm"},{"id":"2506.03079","title":"ORV: 4D Occupancy-centric Robot Video Generation","created":"2025-06-03","cited_by_count":17,"area":"wm"},{"id":"2512.21714","title":"AstraNav-World: World Model for Foresight Control and Consistency","created":"2025-12-25","cited_by_count":17,"area":"wm"},{"id":"2606.01955","title":"WALL-WM: Carving World Action Modeling at the Event Joints","created":"2026-06-01","cited_by_count":17,"area":"wm"},{"id":"2608.04404","title":"Faster-WAM: Efficient Inference-Time Future Conditioning for Robust World Action Models","created":"2026-08-05","cited_by_count":17,"area":"wm"},{"id":"2602.10983","title":"Scaling World Model for Hierarchical Manipulation Policies","created":"2026-02-11","cited_by_count":16,"area":"wm"},{"id":"2511.02097","title":"A Step Toward World Models: A Survey on Robotic Manipulation","created":"2025-10-31","cited_by_count":15,"area":"wm"},{"id":"2511.21690","title":"TraceGen: World Modeling in 3D Trace Space Enables Learning from Cross-Embodiment Videos","created":"2025-11-26","cited_by_count":15,"area":"wm"},{"id":"2603.17808","title":"EVA: Aligning Video World Models with Executable Robot Actions via Inverse Dynamics Rewards","created":"2026-03-18","cited_by_count":14,"area":"wm"},{"id":"2604.14732","title":"World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems","created":"2026-04-16","cited_by_count":14,"area":"wm"},{"id":"2606.17030","title":"Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation","created":"2026-06-15","cited_by_count":14,"area":"wm"},{"id":"2510.26433","title":"Co-Evolving Latent Action World Models","created":"2025-10-30","cited_by_count":13,"area":"wm"},{"id":"2604.22152","title":"dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model","created":"2026-04-24","cited_by_count":13,"area":"wm"},{"id":"2606.20562","title":"MemoryWAM: Efficient World Action Modeling with Persistent Memory","created":"2026-06-18","cited_by_count":13,"area":"wm"},{"id":"2608.26103","title":"Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization","created":"2026-08-26","cited_by_count":13,"area":"wm"},{"id":"2603.25685","title":"Persistent Robot World Models: Stabilizing Multi-Step Rollouts via Reinforcement Learning","created":"2026-03-26","cited_by_count":12,"area":"wm"},{"id":"2505.20425","title":"OSVI-WM: One-Shot Visual Imitation for Unseen Tasks using World-Model-Guided Trajectory Generation","created":"2025-05-26","cited_by_count":11,"area":"wm"},{"id":"2510.05057","title":"StaMo: Unsupervised Learning of Generalizable Robot Motion from Compact State Representation","created":"2025-10-06","cited_by_count":11,"area":"wm"},{"id":"2512.11797","title":"AnchorDream: Repurposing Video Diffusion for Embodiment-Aware Robot Data Synthesis","created":"2025-12-12","cited_by_count":11,"area":"wm"},{"id":"2512.23162","title":"Cosmos-H-Surgical: Learning Surgical Robot Policies from Videos via World Modeling","created":"2025-12-29","cited_by_count":11,"area":"wm"},{"id":"2603.03195","title":"Chain of World: World Model Thinking in Latent Motion","created":"2026-03-03","cited_by_count":11,"area":"wm"},{"id":"2605.07514","title":"Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models","created":"2026-05-08","cited_by_count":11,"area":"wm"},{"id":"2606.17046","title":"Geometric Action Model for Robot Policy Learning","created":"2026-06-15","cited_by_count":11,"area":"wm"},{"id":"2606.23085","title":"Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents","created":"2026-06-22","cited_by_count":11,"area":"wm"},{"id":"2607.02642","title":"GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation","created":"2026-07-02","cited_by_count":11,"area":"wm"},{"id":"2607.13960","title":"GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch","created":"2026-07-15","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":"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":"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":"2507.01424","title":"TriVLA: A Triple-System-Based Unified Vision-Language-Action Model with Episodic World Modeling for General Robot Control","created":"2025-07-02","cited_by_count":9,"area":"wm"},{"id":"2605.29360","title":"MiraBench: Evaluating Action-Conditioned Reliability in Robotic World Models","created":"2026-05-28","cited_by_count":9,"area":"wm"},{"id":"2606.02486","title":"Intercepting the Future: Latent-Space Predictive World Model for Dynamic VLA Manipulation","created":"2026-06-01","cited_by_count":9,"area":"wm"},{"id":"2608.02365","title":"Faster-WAM: Do World Action Models Need Deep Action Modules?","created":"2026-08-03","cited_by_count":9,"area":"wm"},{"id":"2608.03701","title":"LiLa-WAM: Lightweight Latent Reasoning World-Action Model for Robotic Manipulation","created":"2026-08-04","cited_by_count":9,"area":"wm"},{"id":"2603.10422","title":"World2Act: Latent Action Post-Training from World Model Dynamics","created":"2026-03-11","cited_by_count":8,"area":"wm"},{"id":"2604.21017","title":"Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics","created":"2026-04-22","cited_by_count":8,"area":"wm"},{"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":"2607.04927","title":"DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation","created":"2026-07-06","cited_by_count":8,"area":"wm"},{"id":"2602.10717","title":"Say, Dream, and Act: Learning Video World Models for Instruction-Driven Robot Manipulation","created":"2026-02-11","cited_by_count":7,"area":"wm"},{"id":"2602.11291","title":"H-WM: Robotic Task and Motion Planning Guided by Hierarchical World Model","created":"2026-02-11","cited_by_count":7,"area":"wm"},{"id":"2602.19634","title":"Compositional Planning with Jumpy World Models","created":"2026-02-23","cited_by_count":7,"area":"wm"},{"id":"2604.11351","title":"WM-DAgger: Enabling Efficient Data Aggregation for Imitation Learning with World Models","created":"2026-04-13","cited_by_count":7,"area":"wm"},{"id":"2605.07794","title":"NoiseGate: Learning Per-Latent Timestep Schedules as Information Gating in World Action Models","created":"2026-05-08","cited_by_count":7,"area":"wm"},{"id":"2508.20840","title":"Learning Primitive Embodied World Models: Towards Scalable Robotic Learning","created":"2025-08-28","cited_by_count":6,"area":"wm"},{"id":"2604.09330","title":"VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis","created":"2026-04-10","cited_by_count":6,"area":"wm"},{"id":"2605.07931","title":"One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy","created":"2026-05-08","cited_by_count":6,"area":"wm"},{"id":"2606.01600","title":"RoboTrustBench: Benchmarking the Trustworthiness of Video World Models for Robotic Manipulation","created":"2026-06-01","cited_by_count":6,"area":"wm"},{"id":"2607.27599","title":"World Action Planner: Generalizable Decision-Making with Action-Conditioned World Models","created":"2026-07-30","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":"2505.18780","title":"DreamPolicy: A Unified World-model Policy for Scalable Humanoid Locomotion","created":"2025-05-24","cited_by_count":5,"area":"wm"},{"id":"2604.16484","title":"DexWorldModel: Causal Latent World Modeling towards Automated Learning of Embodied Tasks","created":"2026-04-13","cited_by_count":5,"area":"wm"},{"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":"2605.22446","title":"Pre-VLA: Preemptive Runtime Verification for Reliable Vision-Language-Action and World-Model Rollouts","created":"2026-05-21","cited_by_count":5,"area":"wm"},{"id":"2606.27677","title":"DIM-WAM: World-Action Modeling with Diverse Historical Event Memory","created":"2026-06-26","cited_by_count":5,"area":"wm"},{"id":"2609.02531","title":"Spatially Aware World Action Model via Geometric Latent Diffusion","created":"2026-09-02","cited_by_count":5,"area":"wm"},{"id":"2609.05588","title":"GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation","created":"2026-09-04","cited_by_count":5,"area":"wm"},{"id":"2603.20607","title":"Towards Practical World Model-based Reinforcement Learning for Vision-Language-Action Models","created":"2026-03-21","cited_by_count":4,"area":"wm"},{"id":"2605.07288","title":"Sword: Style-Robust World Models as Simulators via Dynamic Latent Bootstrapping for VLA Policy Post-Training","created":"2026-05-08","cited_by_count":4,"area":"wm"},{"id":"2607.01060","title":"RoboWorld: Fast and Reliable Neural Simulators for Generalist Robot Policy Evaluation","created":"2026-07-01","cited_by_count":4,"area":"wm"},{"id":"2607.27924","title":"ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow","created":"2026-07-30","cited_by_count":4,"area":"wm"},{"id":"2608.00793","title":"DynamicWAM: Dual-Path Motion Conditioning for World-Action Models in Dynamic Manipulation","created":"2026-08-01","cited_by_count":4,"area":"wm"},{"id":"2608.01397","title":"SG-WAM: Self-Guided World Modeling in Geometry-Aware Policy Space","created":"2026-08-02","cited_by_count":4,"area":"wm"},{"id":"2608.11605","title":"Foresight Without Seeing: Latent Futures for World Action Models","created":"2026-08-12","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":"2609.00188","title":"ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training","created":"2026-08-31","cited_by_count":4,"area":"wm"},{"id":"2609.04193","title":"GIFT: Guided Intermediate Feature Training via Action-Oriented Structural Supervision for Robotic Manipulation","created":"2026-09-03","cited_by_count":4,"area":"wm"}],"next_cursor":"100"}