{"total":95,"rows":[{"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":"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":"2510.26583","title":"Emu3.5: Native Multimodal Models are World Learners","created":"2025-10-30","cited_by_count":132,"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":"2604.26694","title":"Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising","created":"2026-04-29","cited_by_count":71,"area":"wm"},{"id":"2509.22642","title":"WoW: Towards a World omniscient World model Through Embodied Interaction","created":"2025-09-26","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":"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":"2511.19861","title":"GigaWorld-0: World Models as Data Engine to Empower Embodied AI","created":"2025-11-25","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":"2605.00080","title":"World Model for Robot Learning: A Comprehensive Survey","created":"2026-04-30","cited_by_count":46,"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":"2506.23135","title":"RoboScape: Physics-informed Embodied World Model","created":"2025-06-29","cited_by_count":40,"area":"wm"},{"id":"2506.06199","title":"3DFlowAction: Learning Cross-Embodiment Manipulation from 3D Flow World Model","created":"2025-06-06","cited_by_count":37,"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":"2511.09057","title":"PAN: A World Model for General, Actionable, and Long-Horizon World Simulation","created":"2025-11-12","cited_by_count":36,"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":"2603.23376","title":"ABot-PhysWorld: Interactive World Foundation Model for Robotic Manipulation with Physics Alignment","created":"2026-03-24","cited_by_count":29,"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":"2512.23541","title":"Act2Goal: From World Model To General Goal-conditioned Policy","created":"2025-12-29","cited_by_count":20,"area":"wm"},{"id":"2602.03793","title":"BridgeV2W: Bridging Video Generation Models to Embodied World Models via Embodiment Masks","created":"2026-02-03","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":"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":"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":"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":"2606.13674","title":"RepWAM: World Action Modeling with Representation Visual-Action Tokenizers","created":"2026-06-11","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":"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":"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":"2604.26848","title":"STARRY: Spatial-Temporal Action-Centric World Modeling for Robotic Manipulation","created":"2026-04-29","cited_by_count":10,"area":"wm"},{"id":"2605.10942","title":"HarmoWAM: Harmonizing Generalizable and Precise Manipulation via Adaptive World Action Models","created":"2026-05-11","cited_by_count":10,"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":"2509.21790","title":"LongScape: Advancing Long-Horizon Embodied World Models with Context-Aware MoE","created":"2025-09-26","cited_by_count":7,"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":"2604.09330","title":"VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis","created":"2026-04-10","cited_by_count":6,"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":"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":"2606.27374","title":"World Action Models Enable Continual Imitation Learning with Recurrent Generative Replays","created":"2026-06-25","cited_by_count":4,"area":"wm"},{"id":"2607.11643","title":"Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model","created":"2026-07-13","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":"2608.27033","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":"2602.01630","title":"Research on World Models Is Not Merely Injecting World Knowledge into Specific Tasks","created":"2026-02-02","cited_by_count":3,"area":"wm"},{"id":"2605.15391","title":"PanoWorld: Geometry-Consistent Panoramic Video World Modeling","created":"2026-05-14","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":"2607.11270","title":"Towards Predictive, Aligned, and Scalable Robot Learning","created":"2026-07-13","cited_by_count":3,"area":"wm"},{"id":"2603.25887","title":"World Reasoning Arena","created":"2026-03-26","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":"2607.28624","title":"PhiZero: A World Model Built Around Physical Language","created":"2026-07-30","cited_by_count":2,"area":"wm"},{"id":"2609.11561","title":"Memory as Plans: World-Action Modeling with Memory-Grounded Planning","created":"2026-09-10","cited_by_count":2,"area":"wm"},{"id":"2604.20246","title":"Cortex 2.0: Grounding World Models in Real-World Industrial Deployment","created":"2026-04-22","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":"2606.07089","title":"Dreaming when Necessary: Advancing World Action Models with Adaptive Multi-Modal Reasoning","created":"2026-06-05","cited_by_count":1,"area":"wm"},{"id":"2606.28804","title":"ViPSim: Collaborating Visual and Parameter Spaces for Consistent Long-Horizon Embodied World Models","created":"2026-06-27","cited_by_count":1,"area":"wm"},{"id":"2607.02840","title":"TACO: TActile World Model as a Self-COrrector for Scalable Robot Policy Post-Training","created":"2026-07-03","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":"2607.11689","title":"From World Action Models to Embodied Brains: A Roadmap for Open-World Physical Intelligence","created":"2026-07-13","cited_by_count":1,"area":"wm"},{"id":"2607.16602","title":"PAVXploreRL: Physical-Action-Visual World Model Reinforcement Learning with Action Exploration","created":"2026-07-18","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":"2608.17209","title":"Teach and Grow: An Agent-Centered Architecture for General Robot Learning","created":"2026-08-17","cited_by_count":1,"area":"wm"},{"id":"2609.12036","title":"Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence","created":"2026-09-10","cited_by_count":1,"area":"wm"},{"id":"2609.23184","title":"CausalWM: Causal Chain-of-Thought Reasoning for Embodied World Model","created":"2026-09-19","cited_by_count":1,"area":"wm"},{"id":"2610.10528","title":"Long-WAM: Scaling the Context of World-Action Models","created":"2026-10-07","cited_by_count":1,"area":"wm"},{"id":"2607.00310","title":"RetailSMV: Exocentric vs. Egocentric Adaptation of Foundation Video World Models in Retail","created":"2026-07-01","cited_by_count":0,"area":"wm"},{"id":"2607.04112","title":"DynaVieW: Schema-Guided World Modeling for Understanding Hierarchical Visual Dynamics","created":"2026-07-05","cited_by_count":0,"area":"wm"},{"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":"2607.18709","title":"RoboInter1.5: A Holistic Intermediate Representation Suite for Embodied World Modeling and Robotic Manipulation","created":"2026-07-21","cited_by_count":0,"area":"wm"},{"id":"2608.26239","title":"WALL-SS: Scaling Long-horizon World Models via Next-Scale Autoregression","created":"2026-08-26","cited_by_count":0,"area":"wm"},{"id":"2609.18430","title":"StrucPhysVideo: Learning Physical Dynamics from Structured Captions and Robot Actions","created":"2026-09-16","cited_by_count":0,"area":"wm"},{"id":"2609.24308","title":"HappyWorld-Bench","created":"2026-09-21","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":"2609.27656","title":"InternW0: A Foundational Physical World Model for Efficient Real-World Interactions","created":"2026-09-23","cited_by_count":0,"area":"wm"},{"id":"2609.33464","title":"VIDEAS: Distilling Explicit Action Semantics from Demonstration Videos for World Models via Prior-Guided Simulation","created":"2026-09-27","cited_by_count":0,"area":"wm"},{"id":"2610.01162","title":"PhysicsLENS: Diagnosing Physical Property Blindness in Video Generation Models","created":"2026-10-01","cited_by_count":0,"area":"wm"},{"id":"2610.01559","title":"Completion Aware Guidance for World Action Models","created":"2026-10-01","cited_by_count":0,"area":"wm"},{"id":"2610.02508","title":"World Action Modeling with Progressive Visual Planning","created":"2026-10-01","cited_by_count":0,"area":"wm"},{"id":"2610.03374","title":"EVEWorld: Physical Evolution Supervision for Embodied World Models","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":"2610.07922","title":"OpenWAM: An Open Framework for Composable World-Action Models","created":"2026-10-06","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":"2610.10515","title":"RoboJEPA: Scaling Robotic Latent World Models","created":"2026-10-07","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":"2610.18826","title":"WorldOracle: Benchmarking Action-Conditioned World Models against Real-World Executions","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}