{"total":69,"rows":[{"id":"2510.16732","title":"A Comprehensive Survey on World Models for Embodied AI","created":"2025-10-19","cited_by_count":68,"area":"wm"},{"id":"2509.07996","title":"3D and 4D World Modeling: A Survey","created":"2025-09-04","cited_by_count":67,"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":"2512.23421","title":"DriveLaW:Unifying Planning and Video Generation in a Latent Driving World","created":"2025-12-29","cited_by_count":47,"area":"wm"},{"id":"2602.02393","title":"Infinite-World: Scaling Interactive World Models to 1000-Frame Horizons via Pose-Free Hierarchical Memory","created":"2026-02-02","cited_by_count":40,"area":"wm"},{"id":"2602.06521","title":"DriveWorld-VLA: Unified Latent-Space World Modeling with Vision-Language-Action for Autonomous Driving","created":"2026-02-06","cited_by_count":37,"area":"wm"},{"id":"2510.18313","title":"OmniNWM: Omniscient Driving Navigation World Models","created":"2025-10-21","cited_by_count":33,"area":"wm"},{"id":"2603.24581","title":"Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving","created":"2026-03-25","cited_by_count":33,"area":"wm"},{"id":"2604.04198","title":"DriveVA: Video Action Models are Zero-Shot Drivers","created":"2026-04-05","cited_by_count":23,"area":"wm"},{"id":"2512.19133","title":"WorldRFT: Latent World Model Planning with Reinforcement Fine-Tuning for Autonomous Driving","created":"2025-12-22","cited_by_count":20,"area":"wm"},{"id":"2601.04453","title":"UniDrive-WM: Unified Understanding, Planning and Generation World Model for Autonomous Driving","created":"2026-01-07","cited_by_count":20,"area":"wm"},{"id":"2508.03692","title":"LiDARCrafter: Dynamic 4D World Modeling from LiDAR Sequences","created":"2025-08-05","cited_by_count":17,"area":"wm"},{"id":"2604.01765","title":"DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning","created":"2026-04-02","cited_by_count":17,"area":"wm"},{"id":"2605.09701","title":"DriveFuture: Future-Aware Latent World Models for Autonomous Driving","created":"2026-05-10","cited_by_count":17,"area":"wm"},{"id":"2511.08585","title":"Simulating the Visual World with Artificial Intelligence: A Roadmap","created":"2025-11-11","cited_by_count":15,"area":"wm"},{"id":"2605.14696","title":"EponaV2: Driving World Model with Comprehensive Future Reasoning","created":"2026-05-14","cited_by_count":15,"area":"wm"},{"id":"2510.08713","title":"Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight","created":"2025-10-09","cited_by_count":14,"area":"wm"},{"id":"2511.20325","title":"AD-R1: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving with Impartial World Models","created":"2025-11-25","cited_by_count":14,"area":"wm"},{"id":"2605.28544","title":"DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving","created":"2026-05-27","cited_by_count":14,"area":"wm"},{"id":"2603.14948","title":"Bridging Scene Generation and Planning: Driving with World Model via Unifying Vision and Motion Representation","created":"2026-03-16","cited_by_count":13,"area":"wm"},{"id":"2604.02714","title":"ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving","created":"2026-04-03","cited_by_count":12,"area":"wm"},{"id":"2605.10426","title":"CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving","created":"2026-05-11","cited_by_count":12,"area":"wm"},{"id":"2512.12751","title":"GenieDrive: Towards Physics-Aware Driving World Model with 4D Occupancy Guided Video Generation","created":"2025-12-14","cited_by_count":11,"area":"wm"},{"id":"2603.27287","title":"Uni-World VLA: Interleaved World Modeling and Planning for Autonomous Driving","created":"2026-03-28","cited_by_count":11,"area":"wm"},{"id":"2606.15869","title":"Metis: A Generalizable and Efficient World-Action Model for Autonomous Driving and Urban Navigation","created":"2026-06-14","cited_by_count":11,"area":"wm"},{"id":"2607.05133","title":"UNIVERSE: Unified Video Action Models for Autonomous Driving with Flexible Mask-Modulated Modality Generation","created":"2026-07-06","cited_by_count":9,"area":"wm"},{"id":"2608.07468","title":"SimWAM: A Simple World Action Model for End-to-End Autonomous Driving","created":"2026-08-07","cited_by_count":9,"area":"wm"},{"id":"2606.01164","title":"Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends","created":"2026-05-31","cited_by_count":8,"area":"wm"},{"id":"2512.11226","title":"FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Model","created":"2025-12-12","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":"2606.16274","title":"GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Driving","created":"2026-06-15","cited_by_count":6,"area":"wm"},{"id":"2603.28489","title":"Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms","created":"2026-03-30","cited_by_count":5,"area":"wm"},{"id":"2511.20095","title":"WPT: World-to-Policy Transfer via Online World Model Distillation","created":"2025-11-25","cited_by_count":4,"area":"wm"},{"id":"2603.21104","title":"CounterScene: Counterfactual Causal Reasoning in Generative World Models for Safety-Critical Closed-Loop Evaluation","created":"2026-03-22","cited_by_count":4,"area":"wm"},{"id":"2605.11596","title":"HorizonDrive: Self-Corrective Autoregressive World Model for Long-horizon Driving Simulation","created":"2026-05-12","cited_by_count":4,"area":"wm"},{"id":"2602.01536","title":"UniDWM: Towards a Unified Driving World Model via Multifaceted Representation Learning","created":"2026-02-02","cited_by_count":3,"area":"wm"},{"id":"2603.09086","title":"Latent World Models for Automated Driving: A Unified Taxonomy, Evaluation Framework, and Open Challenges","created":"2026-03-10","cited_by_count":3,"area":"wm"},{"id":"2604.28196","title":"HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation","created":"2026-04-30","cited_by_count":3,"area":"wm"},{"id":"2606.29908","title":"Pondering the Way: Spatial-perceiving World Action Model for Embodied Navigation","created":"2026-06-29","cited_by_count":3,"area":"wm"},{"id":"2608.04964","title":"WorldCycle: Self-Verifiable Reinforcement Learning for Long-Horizon Video World Models","created":"2026-08-05","cited_by_count":3,"area":"wm"},{"id":"2608.23486","title":"GeoWAM: Visual Geometry World Action Models for Autonomous Driving","created":"2026-08-24","cited_by_count":3,"area":"wm"},{"id":"2509.11959","title":"Learning to Generate 4D LiDAR Sequences","created":"2025-09-15","cited_by_count":2,"area":"wm"},{"id":"2603.19675","title":"DynFlowDrive: Flow-Based Dynamic World Modeling for Autonomous Driving","created":"2026-03-20","cited_by_count":2,"area":"wm"},{"id":"2603.24835","title":"DCARL: A Divide-and-Conquer Framework for Autoregressive Long-Trajectory Video Generation","created":"2026-03-25","cited_by_count":2,"area":"wm"},{"id":"2606.27504","title":"ReWorld: Representation Learning for World Action Models","created":"2026-06-25","cited_by_count":2,"area":"wm"},{"id":"2607.07196","title":"Validate the Dream Before You Trust Its Verdict: Admissibility for World-Model Simulators","created":"2026-07-08","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":"2609.07328","title":"PV-WM: A Heterogeneous Micro-Macro World Model for Articulated Pedestrian-Vehicle Co-Rollout","created":"2026-09-07","cited_by_count":2,"area":"wm"},{"id":"2510.24785","title":"Semantic Communications with World Models","created":"2025-10-27","cited_by_count":1,"area":"wm"},{"id":"2512.08478","title":"Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform","created":"2025-12-09","cited_by_count":1,"area":"wm"},{"id":"2602.23259","title":"Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving","created":"2026-02-26","cited_by_count":1,"area":"wm"},{"id":"2606.00267","title":"StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement","created":"2026-05-29","cited_by_count":1,"area":"wm"},{"id":"2606.01935","title":"Unified Driving Tokens: Representation- and Geometry-Guided Discrete Tokenizer for Driving World Models and Planning","created":"2026-06-01","cited_by_count":1,"area":"wm"},{"id":"2606.28757","title":"A Physics-Grounded Benchmark for Multi-Agent Dynamics in World Models","created":"2026-06-27","cited_by_count":1,"area":"wm"},{"id":"2607.10630","title":"World Models as Adversaries: Multi-Agent Self-Play Fine-Tuning for Robust Motion Planning","created":"2026-07-12","cited_by_count":1,"area":"wm"},{"id":"2610.13781","title":"SimVTA: Simulation-Grounded Video-Trajectory Alignment for Driving World Action Models","created":"2026-10-09","cited_by_count":1,"area":"wm"},{"id":"2511.18735","title":"Thinking Ahead: Foresight Intelligence in MLLMs and World Model","created":"2025-11-24","cited_by_count":0,"area":"wm"},{"id":"2603.28887","title":"OccSim: Multi-kilometer Simulation with Long-horizon Occupancy World Models","created":"2026-03-30","cited_by_count":0,"area":"wm"},{"id":"2605.22089","title":"LVDrive: Latent Visual Representation Enhanced Vision-Language-Action Autonomous Driving Model","created":"2026-05-21","cited_by_count":0,"area":"wm"},{"id":"2606.13840","title":"Multi-Agent Embodied Autonomous Driving (MAEAD): From V2X Information Exchange to Shared World Models","created":"2026-06-11","cited_by_count":0,"area":"wm"},{"id":"2607.10781","title":"Is Energy Guidance All You Need? Training-Free Norm Injection for Driving World Models","created":"2026-07-12","cited_by_count":0,"area":"wm"},{"id":"2607.15898","title":"Orbis 2: A Hierarchical World Model for Driving","created":"2026-07-17","cited_by_count":0,"area":"wm"},{"id":"2609.21712","title":"ZYT-World: A Real-Time Controllable World Model for Closed-Loop Autonomous-Driving Simulation","created":"2026-09-18","cited_by_count":0,"area":"wm"},{"id":"2609.28931","title":"HelloWorld: Towards Practical Applications of Generative Driving World Models","created":"2026-09-24","cited_by_count":0,"area":"wm"},{"id":"2609.30436","title":"WALT: Learning World-Model-Aligned Latent Trajectories for Autonomous Driving","created":"2026-09-24","cited_by_count":0,"area":"wm"},{"id":"2609.33264","title":"VehDyn: A Driving World Model Benchmark for Vehicle Dynamics","created":"2026-09-27","cited_by_count":0,"area":"wm"},{"id":"2609.34085","title":"AD-E2E-JEPA: A Joint-Embedding Predictive Architecture For End-to-End Autonomous Driving","created":"2026-09-28","cited_by_count":0,"area":"wm"},{"id":"2609.36851","title":"RoXDrive: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving via Action-Faithful Rollouts","created":"2026-09-29","cited_by_count":0,"area":"wm"},{"id":"2609.37970","title":"PhysWAM: Physically Consistent World Action Model for Autonomous Driving","created":"2026-09-29","cited_by_count":0,"area":"wm"}],"next_cursor":null}