{"total":79,"rows":[{"id":"2212.09748","title":"Scalable Diffusion Models with Transformers","created":"2022-12-19","cited_by_count":6054,"area":"wm"},{"id":"2311.15127","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","created":"2023-11-25","cited_by_count":2581,"area":"wm"},{"id":"2408.06072","title":"CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer","created":"2024-08-12","cited_by_count":2261,"area":"wm"},{"id":"2202.04200","title":"MaskGIT: Masked Generative Image Transformer","created":"2022-02-08","cited_by_count":1099,"area":"wm"},{"id":"2309.17080","title":"GAIA-1: A Generative World Model for Autonomous Driving","created":"2023-09-29","cited_by_count":637,"area":"wm"},{"id":"2506.21539","title":"WorldVLA: Towards Autoregressive Action World Model","created":"2025-06-26","cited_by_count":367,"area":"wm"},{"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":"2212.05199","title":"MAGVIT: Masked Generative Video Transformer","created":"2022-12-10","cited_by_count":346,"area":"wm"},{"id":"2209.00588","title":"Transformers are Sample-Efficient World Models","created":"2022-09-01","cited_by_count":328,"area":"wm"},{"id":"2503.21755","title":"VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness","created":"2025-03-27","cited_by_count":315,"area":"wm"},{"id":"2405.12399","title":"Diffusion for World Modeling: Visual Details Matter in Atari","created":"2024-05-20","cited_by_count":300,"area":"wm"},{"id":"2403.14773","title":"StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text","created":"2024-03-21","cited_by_count":251,"area":"wm"},{"id":"2402.08268","title":"World Model on Million-Length Video And Language With Blockwise RingAttention","created":"2024-02-13","cited_by_count":198,"area":"wm"},{"id":"2503.20523","title":"GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving","created":"2025-03-26","cited_by_count":185,"area":"wm"},{"id":"2403.09630","title":"GenAD: Generalized Predictive Model for Autonomous Driving","created":"2024-03-14","cited_by_count":150,"area":"wm"},{"id":"2405.15223","title":"iVideoGPT: Interactive VideoGPTs are Scalable World Models","created":"2024-05-24","cited_by_count":146,"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":"2506.24113","title":"Epona: Autoregressive Diffusion World Model for Autonomous Driving","created":"2025-06-30","cited_by_count":117,"area":"wm"},{"id":"2406.14540","title":"IRASim: A Fine-Grained World Model for Robot Manipulation","created":"2024-06-20","cited_by_count":100,"area":"wm"},{"id":"2504.08388","title":"MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft","created":"2025-04-11","cited_by_count":97,"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":"2401.09985","title":"WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens","created":"2024-01-18","cited_by_count":89,"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":"2404.00815","title":"Towards Realistic Scene Generation with LiDAR Diffusion Models","created":"2024-03-31","cited_by_count":69,"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":"2412.19505","title":"DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT","created":"2024-12-27","cited_by_count":66,"area":"wm"},{"id":"2508.18269","title":"FlowVLA: Visual Chain of Thought-based Motion Reasoning for Vision-Language-Action Models","created":"2025-08-25","cited_by_count":50,"area":"wm"},{"id":"2403.10094","title":"RangeLDM: Fast Realistic LiDAR Point Cloud Generation","created":"2024-03-15","cited_by_count":47,"area":"wm"},{"id":"2505.13934","title":"RLVR-World: Training World Models with Reinforcement Learning","created":"2025-05-20","cited_by_count":40,"area":"wm"},{"id":"2602.22010","title":"World Guidance: World Modeling in Condition Space for Action Generation","created":"2026-02-25","cited_by_count":36,"area":"wm"},{"id":"2502.15672","title":"VaViM and VaVAM: Autonomous Driving through Video Generative Modeling","created":"2025-02-21","cited_by_count":35,"area":"wm"},{"id":"2506.02327","title":"Medical World Model: Generative Simulation of Tumor Evolution for Treatment Planning","created":"2025-06-02","cited_by_count":34,"area":"wm"},{"id":"2406.19320","title":"Efficient World Models with Context-Aware Tokenization","created":"2024-06-27","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":"2307.02064","title":"Facing Off World Model Backbones: RNNs, Transformers, and S4","created":"2023-07-05","cited_by_count":31,"area":"wm"},{"id":"2305.10912","title":"A Generalist Dynamics Model for Control","created":"2023-05-18","cited_by_count":24,"area":"wm"},{"id":"2411.04434","title":"Scaling Laws for Pre-training Agents and World Models","created":"2024-11-07","cited_by_count":23,"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":"2507.13162","title":"Orbis: Overcoming Challenges of Long-Horizon Prediction in Driving World Models","created":"2025-07-17","cited_by_count":17,"area":"wm"},{"id":"2512.05927","title":"World Models That Know When They Don't Know - Controllable Video Generation with Calibrated Uncertainty","created":"2025-12-05","cited_by_count":17,"area":"wm"},{"id":"2603.04553","title":"Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling","created":"2026-03-04","cited_by_count":15,"area":"wm"},{"id":"2410.00564","title":"Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining","created":"2024-10-01","cited_by_count":14,"area":"wm"},{"id":"2304.02639","title":"ENTL: Embodied Navigation Trajectory Learner","created":"2023-04-05","cited_by_count":11,"area":"wm"},{"id":"2312.01203","title":"Harnessing Discrete Representations For Continual Reinforcement Learning","created":"2023-12-02","cited_by_count":11,"area":"wm"},{"id":"2402.05643","title":"Improving Token-Based World Models with Parallel Observation Prediction","created":"2024-02-08","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":"2604.09059","title":"Learning Vision-Language-Action World Models for Autonomous Driving","created":"2026-04-10","cited_by_count":11,"area":"wm"},{"id":"2604.04913","title":"A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens","created":"2026-04-06","cited_by_count":10,"area":"wm"},{"id":"2503.00653","title":"Discrete Codebook World Models for Continuous Control","created":"2025-03-01","cited_by_count":9,"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":"2401.14718","title":"A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches","created":"2024-01-26","cited_by_count":7,"area":"wm"},{"id":"2502.05857","title":"EgoAgent: A Joint Predictive Agent Model in Egocentric Worlds","created":"2025-02-09","cited_by_count":7,"area":"wm"},{"id":"2507.04075","title":"Accurate and Efficient World Modeling with Masked Latent Transformers","created":"2025-07-05","cited_by_count":7,"area":"wm"},{"id":"2509.09737","title":"World Modeling with Probabilistic Structure Integration","created":"2025-09-10","cited_by_count":7,"area":"wm"},{"id":"2604.06339","title":"Evolution of Video Generative Foundations","created":"2026-04-07","cited_by_count":7,"area":"wm"},{"id":"2406.01361","title":"Learning to Play Atari in a World of Tokens","created":"2024-06-03","cited_by_count":6,"area":"wm"},{"id":"2502.11537","title":"Simulus: Combining Improvements in Sample-Efficient World Model Agents","created":"2025-02-17","cited_by_count":6,"area":"wm"},{"id":"2603.05438","title":"Planning in 8 Tokens: A Compact Discrete Tokenizer for Latent World Model","created":"2026-03-05","cited_by_count":6,"area":"wm"},{"id":"2404.05505","title":"Taming Transformers for Realistic Lidar Point Cloud Generation","created":"2024-04-08","cited_by_count":5,"area":"wm"},{"id":"2506.23074","title":"Learning Counterfactually Decoupled Attention for Open-World Model Attribution","created":"2025-06-29","cited_by_count":5,"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":"2407.13466","title":"LIMT: Language-Informed Multi-Task Visual World Models","created":"2024-07-18","cited_by_count":4,"area":"wm"},{"id":"2509.15536","title":"SAMPO:Scale-wise Autoregression with Motion PrOmpt for generative world models","created":"2025-09-19","cited_by_count":4,"area":"wm"},{"id":"2607.25242","title":"Medical world models in healthcare: foundations, applications, and challenges for trustworthy clinical translation","created":"2026-07-28","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":"2404.18896","title":"Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models","created":"2024-04-29","cited_by_count":2,"area":"wm"},{"id":"2506.23606","title":"SG-LDM: Semantic-Guided LiDAR Generation via Latent-Aligned Diffusion","created":"2025-06-30","cited_by_count":2,"area":"wm"},{"id":"2605.24321","title":"Unified 3D Scene Understanding Through Physical World Modeling","created":"2026-05-23","cited_by_count":2,"area":"wm"},{"id":"2506.17967","title":"Adapting Vision-Language Models for Evaluating World Models","created":"2025-06-22","cited_by_count":1,"area":"wm"},{"id":"2509.15479","title":"OpenViGA: Video Generation for Automotive Driving Scenes by Streamlining and Fine-Tuning Open Source Models with Public Data","created":"2025-09-18","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":"2405.20180","title":"Transformers and Slot Encoding for Sample Efficient Physical World Modelling","created":"2024-05-30","cited_by_count":0,"area":"wm"},{"id":"2509.23008","title":"ARSS: Taming Decoder-only Autoregressive Visual Generation for View Synthesis From Single View","created":"2025-09-27","cited_by_count":0,"area":"wm"},{"id":"2510.16039","title":"Vector Quantization in the Brain: Grid-like Codes in World Models","created":"2025-10-16","cited_by_count":0,"area":"wm"},{"id":"2511.16049","title":"LiSTAR: Ray-Centric World Models for 4D LiDAR Sequences in Autonomous Driving","created":"2025-11-20","cited_by_count":0,"area":"wm"},{"id":"2511.16484","title":"Flow and Depth Assisted Video Prediction with Latent Transformer","created":"2025-11-20","cited_by_count":0,"area":"wm"},{"id":"2603.19219","title":"DriveTok: 3D Driving Scene Tokenization for Unified Multi-View Reconstruction and Understanding","created":"2026-03-19","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":"2610.14583","title":"Remembering What Matters for Long-Horizon Robotic World Models","created":"2026-10-10","cited_by_count":0,"area":"wm"}],"next_cursor":null}