{"total":121,"rows":[{"id":"2405.17398","title":"Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability","created":"2024-05-27","cited_by_count":347,"area":"wm"},{"id":"2402.11502","title":"GenAD: Generative End-to-End Autonomous Driving","created":"2024-02-18","cited_by_count":225,"area":"wm"},{"id":"2406.08481","title":"Enhancing End-to-End Autonomous Driving with Latent World Model","created":"2024-06-12","cited_by_count":166,"area":"wm"},{"id":"2411.14499","title":"Understanding World or Predicting Future? A Comprehensive Survey of World Models","created":"2024-11-21","cited_by_count":166,"area":"wm"},{"id":"2506.24113","title":"Epona: Autoregressive Diffusion World Model for Autonomous Driving","created":"2025-06-30","cited_by_count":117,"area":"wm"},{"id":"2405.03520","title":"Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond","created":"2024-05-06","cited_by_count":111,"area":"wm"},{"id":"2412.18607","title":"DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers","created":"2024-12-24","cited_by_count":96,"area":"wm"},{"id":"2507.00603","title":"World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model","created":"2025-07-01","cited_by_count":95,"area":"wm"},{"id":"2406.09455","title":"Pandora: Towards General World Model with Natural Language Actions and Video States","created":"2024-06-12","cited_by_count":86,"area":"wm"},{"id":"2409.03272","title":"OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving","created":"2024-09-05","cited_by_count":83,"area":"wm"},{"id":"2403.02622","title":"World Models for Autonomous Driving: An Initial Survey","created":"2024-03-05","cited_by_count":80,"area":"wm"},{"id":"2412.11198","title":"GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control","created":"2024-12-15","cited_by_count":78,"area":"wm"},{"id":"2408.14197","title":"Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving","created":"2024-08-26","cited_by_count":69,"area":"wm"},{"id":"2510.16732","title":"A Comprehensive Survey on World Models for Embodied AI","created":"2025-10-19","cited_by_count":68,"area":"wm"},{"id":"2412.10373","title":"GaussianWorld: Gaussian World Model for Streaming 3D Occupancy Prediction","created":"2024-12-13","cited_by_count":67,"area":"wm"},{"id":"2509.07996","title":"3D and 4D World Modeling: A Survey","created":"2025-09-04","cited_by_count":67,"area":"wm"},{"id":"2412.19505","title":"DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT","created":"2024-12-27","cited_by_count":66,"area":"wm"},{"id":"2410.10429","title":"DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model","created":"2024-10-14","cited_by_count":61,"area":"wm"},{"id":"2501.11260","title":"A Survey of World Models for Autonomous Driving","created":"2025-01-20","cited_by_count":60,"area":"wm"},{"id":"2501.14729","title":"HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation","created":"2025-01-24","cited_by_count":56,"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":"2409.11356","title":"RenderWorld: World Model with Self-Supervised 3D Label","created":"2024-09-17","cited_by_count":46,"area":"wm"},{"id":"2409.18341","title":"Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Driving","created":"2024-09-26","cited_by_count":46,"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":"2506.09981","title":"ReSim: Reliable World Simulation for Autonomous Driving","created":"2025-06-11","cited_by_count":44,"area":"wm"},{"id":"2508.17600","title":"GWM: Towards Scalable Gaussian World Models for Robotic Manipulation","created":"2025-08-25","cited_by_count":39,"area":"wm"},{"id":"2410.18084","title":"DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes","created":"2024-10-23","cited_by_count":38,"area":"wm"},{"id":"2510.18313","title":"OmniNWM: Omniscient Driving Navigation World Models","created":"2025-10-21","cited_by_count":33,"area":"wm"},{"id":"2510.19654","title":"From Forecasting to Planning: Policy World Model for Collaborative State-Action Prediction","created":"2025-10-22","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":"2502.07309","title":"Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving","created":"2025-02-11","cited_by_count":29,"area":"wm"},{"id":"2502.10498","title":"The Role of World Models in Shaping Autonomous Driving: A Comprehensive Survey","created":"2025-02-14","cited_by_count":29,"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":"2407.05679","title":"BEVWorld: A Multimodal World Simulator for Autonomous Driving via Scene-Level BEV Latents","created":"2024-07-08","cited_by_count":21,"area":"wm"},{"id":"2505.19239","title":"DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving","created":"2025-05-25","cited_by_count":21,"area":"wm"},{"id":"2601.01528","title":"DrivingGen: A Comprehensive Benchmark for Generative Video World Models in Autonomous Driving","created":"2026-01-04","cited_by_count":21,"area":"wm"},{"id":"2505.22421","title":"GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control","created":"2025-05-28","cited_by_count":19,"area":"wm"},{"id":"2412.09600","title":"Owl-1: Omni World Model for Consistent Long Video Generation","created":"2024-12-12","cited_by_count":18,"area":"wm"},{"id":"2412.13772","title":"An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training","created":"2024-12-18","cited_by_count":18,"area":"wm"},{"id":"2503.15875","title":"MiLA: Multi-view Intensive-fidelity Long-term Video Generation World Model for Autonomous Driving","created":"2025-03-20","cited_by_count":18,"area":"wm"},{"id":"2410.10394","title":"PIVOT-R: Primitive-Driven Waypoint-Aware World Model for Robotic Manipulation","created":"2024-10-14","cited_by_count":17,"area":"wm"},{"id":"2506.03079","title":"ORV: 4D Occupancy-centric Robot Video Generation","created":"2025-06-03","cited_by_count":17,"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":"2605.09701","title":"DriveFuture: Future-Aware Latent World Models for Autonomous Driving","created":"2026-05-10","cited_by_count":17,"area":"wm"},{"id":"2504.18576","title":"DriVerse: Navigation World Model for Driving Simulation via Multimodal Trajectory Prompting and Motion Alignment","created":"2025-04-22","cited_by_count":16,"area":"wm"},{"id":"2602.10884","title":"ResWorld: Temporal Residual World Model for End-to-End Autonomous Driving","created":"2026-02-11","cited_by_count":15,"area":"wm"},{"id":"2411.02914","title":"Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey","created":"2024-11-05","cited_by_count":14,"area":"wm"},{"id":"2506.13260","title":"COME: Adding Scene-Centric Forecasting Control to Occupancy World Model","created":"2025-06-16","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":"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":"2512.04441","title":"MindDrive: An All-in-One Framework Bridging World Models and Vision-Language Model for End-to-End Autonomous Driving","created":"2025-12-04","cited_by_count":12,"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":"2506.19842","title":"ManiGaussian++: General Robotic Bimanual Manipulation with Hierarchical Gaussian World Model","created":"2025-06-24","cited_by_count":11,"area":"wm"},{"id":"2510.17482","title":"SparseWorld: A Flexible, Adaptive, and Efficient 4D Occupancy World Model Powered by Sparse and Dynamic Queries","created":"2025-10-20","cited_by_count":11,"area":"wm"},{"id":"2604.09059","title":"Learning Vision-Language-Action World Models for Autonomous Driving","created":"2026-04-10","cited_by_count":11,"area":"wm"},{"id":"2503.02143","title":"Four Principles for Physically Interpretable World Models","created":"2025-03-04","cited_by_count":10,"area":"wm"},{"id":"2505.22643","title":"SPIRAL: Semantic-Aware Progressive LiDAR Scene Generation and Understanding","created":"2025-05-28","cited_by_count":10,"area":"wm"},{"id":"2506.23434","title":"Towards foundational LiDAR world models with efficient latent flow matching","created":"2025-06-30","cited_by_count":10,"area":"wm"},{"id":"2506.01546","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","created":"2025-06-02","cited_by_count":9,"area":"wm"},{"id":"2509.03887","title":"OccTENS: 3D Occupancy World Model via Temporal Next-Scale Prediction","created":"2025-09-04","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":"2505.05512","title":"Occupancy World Model for Robots","created":"2025-05-07","cited_by_count":8,"area":"wm"},{"id":"2507.09144","title":"$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting","created":"2025-07-12","cited_by_count":8,"area":"wm"},{"id":"2407.21126","title":"Self-supervised Multi-future Occupancy Forecasting for Autonomous Driving","created":"2024-07-30","cited_by_count":7,"area":"wm"},{"id":"2602.08006","title":"ForecastOcc: Vision-based Semantic Occupancy Forecasting","created":"2026-02-08","cited_by_count":7,"area":"wm"},{"id":"2411.14169","title":"Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting","created":"2024-11-21","cited_by_count":6,"area":"wm"},{"id":"2603.25741","title":"Vega: Learning to Drive with Natural Language Instructions","created":"2026-03-26","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":"2607.26754","title":"StatePlay: State-Aware Game World Models for Mechanics-Consistent Generation","created":"2026-07-29","cited_by_count":6,"area":"wm"},{"id":"2608.14530","title":"Marionette: Predicting World States, Rendering Geometry, Painting Appearance","created":"2026-08-14","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":"2503.07338","title":"Delta-Triplane Transformers as Occupancy World Models","created":"2025-03-10","cited_by_count":5,"area":"wm"},{"id":"2605.18137","title":"Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving","created":"2026-05-18","cited_by_count":5,"area":"wm"},{"id":"2607.29031","title":"Auto-JEPA: A Latent World Model of Continuous Intent for End-to-End Autonomous Driving","created":"2026-07-31","cited_by_count":5,"area":"wm"},{"id":"2505.01729","title":"PosePilot: Steering Camera Pose for Generative World Models with Self-supervised Depth","created":"2025-05-03","cited_by_count":4,"area":"wm"},{"id":"2506.20134","title":"From 2D to 3D Cognition: A Brief Survey of General World Models","created":"2025-06-25","cited_by_count":4,"area":"wm"},{"id":"2510.14977","title":"Terra: Explorable Native 3D World Model with Point Latents","created":"2025-10-16","cited_by_count":4,"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":"2511.22039","title":"SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model","created":"2025-11-27","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":"2412.12870","title":"Physically Interpretable World Models via Weakly Supervised Representation Learning","created":"2024-12-17","cited_by_count":3,"area":"wm"},{"id":"2507.23325","title":"FASTopoWM: Fast-Slow Lane Segment Topology Reasoning with Latent World Models","created":"2025-07-31","cited_by_count":3,"area":"wm"},{"id":"2510.04978","title":"Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI","created":"2025-10-06","cited_by_count":3,"area":"wm"},{"id":"2510.16729","title":"Vision-Centric 4D Occupancy Forecasting and Planning via Implicit Residual World Models","created":"2025-10-19","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":"2606.00133","title":"World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications","created":"2026-05-28","cited_by_count":3,"area":"wm"},{"id":"2608.23486","title":"GeoWAM: Visual Geometry World Action Models for Autonomous Driving","created":"2026-08-24","cited_by_count":3,"area":"wm"},{"id":"2507.04002","title":"NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World Models","created":"2025-07-05","cited_by_count":2,"area":"wm"},{"id":"2509.11959","title":"Learning to Generate 4D LiDAR Sequences","created":"2025-09-15","cited_by_count":2,"area":"wm"},{"id":"2512.03454","title":"Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles","created":"2025-12-03","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":"2603.28963","title":"AutoWorld: Learning Multi-Agent Traffic Simulation with Self-Supervised World Models","created":"2026-03-30","cited_by_count":2,"area":"wm"},{"id":"2604.00969","title":"DLWM: Dual Latent World Models enable Holistic Gaussian-centric Pre-training in Autonomous Driving","created":"2026-04-01","cited_by_count":2,"area":"wm"},{"id":"2604.06882","title":"Telecom World Models: Unifying Digital Twins, Foundation Models, and Predictive Planning for 6G","created":"2026-04-08","cited_by_count":2,"area":"wm"},{"id":"2605.24354","title":"SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation","created":"2026-05-23","cited_by_count":2,"area":"wm"},{"id":"2606.16605","title":"ARB4WM: An Adversarial Robustness Benchmark for World Models in Continuous Control","created":"2026-06-15","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":"2606.30421","title":"OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model","created":"2026-06-29","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"}],"next_cursor":"100"}