This repository provides a curated list of papers for World Models for General Video Generation, Embodied AI, and Autonomous Driving. Template from Awesome-LLM-Robotics and Awesome-World-Model

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  • Overview
  • Foundation paper of World Model
  • Blog or Technical Report
  • Surveys
  • Benchmarks & Evaluation
  • General World Models
  • World Models for Embodied AI
  • World Models for VLA
  • World Models for Visual Understanding
  • World Models for Autonomous Driving
    • Refer to https://github.com/LMD0311/Awesome-World-Model
  • Citation

• World Models, NIPS 2018 Oral. [Paper] [Website]

• SIMA 2, SIMA 2: A Generalist Embodied Agent for Virtual Worlds. [Paper]
• SimWorld, SimWorld: An Open-ended Realistic Simulator for Autonomous Agents in Physical and Social Worlds. [Paper] [Website]
• Hunyuan-GameCraft-2, Hunyuan-GameCraft-2: Instruction-following Interactive Game World Model. [Paper] [Website]
• GigaWorld-0, GigaWorld-0: World Models as Data Engine to Empower Embodied AI. [Paper] [Website]
• PAN, PAN: A World Model for General, Interactable, and Long-Horizon World Simulation. [Paper]
• Cosmos-Predict2.5, World Simulation with Video Foundation Models for Physical AI. [Paper] [Code]
• Emu3.5, Emu3.5: Native Multimodal Models are World Learners. [Paper] [Website] [Code]
• ODesign, ODesign: A World Model for Biomolecular Interaction Design. [Paper] [Website]
• GigaBrain-0, GigaBrain-0: A World Model-Powered Vision-Language-Action Model. [Paper] [Website]
• CWM, CWM: An Open-Weights LLM for Research on Code Generation with World Models. [Paper] [Website] [Code]
• WoW, WoW: Towards a World omniscient World model Through Embodied Interaction. [Paper] [Website]
• Matrix-Game 2.0, Matrix-Game 2.0: An Open-Source, Real-Time, and Streaming Interactive World Model. [Paper] [Website]
• Matrix-3D, Matrix-3D: Omnidirectional Explorable 3D World Generation. [Paper] [Website]
• HunyuanWorld 1.0, HunyuanWorld 1.0: Generating Immersive, Explorable, and Interactive 3D Worlds from Words or Pixels. [Paper] [Website] [Code]
• What Does it Mean for a Neural Network to Learn a "World Model"?. [Paper]
• Matrix-Game, Matrix-Game: Interactive World Foundation Model. [Paper] [Code]
• Cosmos-Drive-Dreams, Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models. [Paper] [Website]
• GAIA-2, GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving. [Paper] [Website]
• Cosmos, Cosmos World Foundation Model Platform for Physical AI. [Paper] [Website] [Code]
• 1X Technologies, 1X World Model. [Blog]
• Runway, Introducing General World Models. [Blog]
• Wayve, Introducing GAIA-1: A Cutting-Edge Generative AI Model for Autonomy. [Paper] [Blog]
• Yann LeCun, A Path Towards Autonomous Machine Intelligence. [Paper]

• "Beyond World Models: Rethinking Understanding in AI Models", AAAI 2026. [Paper]
• "Simulating the Visual World with Artificial Intelligence: A Roadmap", arXiv 2025.11. [Paper] [Wesite] [Code]
• "A Step Toward World Models: A Survey on Robotic Manipulation", arXiv 2025.11. [Paper]
• "World Models Should Prioritize the Unification of Physical and Social Dynamics", NIPS 2025. [Paper] [Website]
• "From Masks to Worlds: A Hitchhiker's Guide to World Models", arXiv 2025.10. [Paper] [Website]
• "A Comprehensive Survey on World Models for Embodied AI", arXiv 2025.10. [Paper] [Website]
• "The Safety Challenge of World Models for Embodied AI Agents: A Review", arXiv 2025.10. [Paper]
• "Embodied AI: From LLMs to World Models", IEEE CASM. [Paper]
• "3D and 4D World Modeling: A Survey", arXiv 2025.09. [Paper]
• "Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges", arXiv 2025.08. [Paper]
• "A Survey: Learning Embodied Intelligence from Physical Simulators and World Models", arXiv 2025.07. [Paper] [Code]
• "Embodied AI Agents: Modeling the World", arXiv 2025.06. [Paper]
• "From 2D to 3D Cognition: A Brief Survey of General World Models", arXiv 2025.06. [Paper]
• "A Survey on World Models Grounded in Acoustic Physical Information", arXiv 2025.06. [Paper]
• "Exploring the Evolution of Physics Cognition in Video Generation: A Survey", arXiv 2025.03. [Paper] [Code]
• "World Models in Artificial Intelligence: Sensing, Learning, and Reasoning Like a Child", arXiv 2025.03. [Paper]
• "Simulating the Real World: A Unified Survey of Multimodal Generative Models", arXiv 2025.03. [Paper] [Code]
• "Four Principles for Physically Interpretable World Models", arXiv 2025.03. [Paper]
• "The Role of World Models in Shaping Autonomous Driving: A Comprehensive Survey", arXiv 2025.02. [Paper] [Code]
• "A Survey of World Models for Autonomous Driving", TPAMI. [Paper]
• "Understanding World or Predicting Future? A Comprehensive Survey of World Models", arXiv 2024.11. [Paper]
• "World Models: The Safety Perspective", ISSRE WDMD. [Paper]
• "Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey", arXiv 2024.11. [Paper]
• "From Efficient Multimodal Models to World Models: A Survey", arXiv 2024.07. [Paper]
• "Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI", arXiv 2024.07. [Paper] [Code]
• "Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond", arXiv 2024.05. [Paper] [Code]
• "World Models for Autonomous Driving: An Initial Survey", TIV. [Paper]
• "A survey on multimodal large language models for autonomous driving", WACVW 2024. [Paper] [Code]

• On Memory: A comparison of memory mechanisms in world models: "On Memory: A comparison of memory mechanisms in world models" World Modeling Workshop 2026. [Paper]
• SmallWorlds: "SmallWorlds: Assessing Dynamics Understanding of World Models in Isolated Environments", arXiv 2025.11. [Paper]
• 4DWorldBench: "4DWorldBench: A Comprehensive Evaluation Framework for 3D/4D World Generation Models", arXiv 2025.11. [Paper]
• Target-Bench: "Target-Bench: Can World Models Achieve Mapless Path Planning with Semantic Targets?", arXiv 2025.11. [Paper]
• PragWorld: "PragWorld: A Benchmark Evaluating LLMs' Local World Model under Minimal Linguistic Alterations and Conversational Dynamics", AAAI 2026. [Paper]
• "Can World Simulators Reason? Gen-ViRe: A Generative Visual Reasoning Benchmark", arXiv 2025.11. [Paper] [Code]
• "Scalable Policy Evaluation with Video World Models", arXiv 2025.11. [Paper]
• "Expert Evaluation of LLM World Models: A High-Tc Superconductivity Case Study", ICML 2025 workshop on Assessing World Models and the Explorations in AI Today. [Paper]
• "Benchmarking World-Model Learning", arXiv 2025.10. [Paper]
• World-in-World: "World-in-World: World Models in a Closed-Loop World", arXiv 2025.10. [Paper] [Website]
• VideoVerse: "VideoVerse: How Far is Your T2V Generator from a World Model?", arXiv 2025.10. [Paper]
• OmniWorld: "OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling", arXiv 2025.09. [Paper] [Website]
• "Beyond Simulation: Benchmarking World Models for Planning and Causality in Autonomous Driving", ICRA 2025. [Paper]
• WM-ABench: "Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation", ACL 2025(Findings). [Paper] [Website]
• UNIVERSE: "Adapting Vision-Language Models for Evaluating World Models", arxiv 2025.06. [Paper]
• WorldPrediction: "WorldPrediction: A Benchmark for High-level World Modeling and Long-horizon Procedural Planning", arxiv 2025.06. [Paper]
• "Toward Memory-Aided World Models: Benchmarking via Spatial Consistency", arxiv 2025.05. [Paper] [Datasets] [Code]
• SimWorld: "SimWorld: A Unified Benchmark for Simulator-Conditioned Scene Generation via World Model", arxiv 2025.05. [Paper] [Code]
• EWMBench: "EWMBench: Evaluating Scene, Motion, and Semantic Quality in Embodied World Models", arxiv 2025.05. [Paper] [Code]
• "Toward Stable World Models: Measuring and Addressing World Instability in Generative Environments", arxiv 2025.03. [Paper]
• WorldModelBench: "WorldModelBench: Judging Video Generation Models As World Models", CVPR 2025. [Paper] [Website]
• Text2World: "Text2World: Benchmarking Large Language Models for Symbolic World Model Generation", arxiv 2025.02. [Paper] [Website]
• ACT-Bench: "ACT-Bench: Towards Action Controllable World Models for Autonomous Driving", arxiv 2024.12. [Paper]
• WorldSimBench: "WorldSimBench: Towards Video Generation Models as World Simulators", arxiv 2024.10. [Paper] [Website]
• EVA: "EVA: An Embodied World Model for Future Video Anticipation", ICML 2025. [Paper] [Website]
• AeroVerse: "AeroVerse: UAV-Agent Benchmark Suite for Simulating, Pre-training, Finetuning, and Evaluating Aerospace Embodied World Models", arxiv 2024.08. [Paper]
• CityBench: "CityBench: Evaluating the Capabilities of Large Language Model as World Model", arXiv 2024.06. [Paper] [Code]
• "Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models", NIPS 2023. [Paper]

• "Closing the Train-Test Gap in World Models for Gradient-Based Planning", `arxiv 2025.12. [Paper]
• WonderZoom: "WonderZoom: Multi-Scale 3D World Generation", `arxiv 2025.12. [Paper] [Website]
• Astra: "Astra: General Interactive World Model with Autoregressive Denoising", `arxiv 2025.12. [Paper] [Website] [Code]
• Visionary: "Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform", `arxiv 2025.12. [Paper] [Website]
• CLARITY: "CLARITY: Medical World Model for Guiding Treatment Decisions by Modeling Context-Aware Disease Trajectories in Latent Space", `arxiv 2025.12. [Paper]
• UnityVideo: "UnityVideo: Unified Multi-Modal Multi-Task Learning for Enhancing World-Aware Video Generation", `arxiv 2025.12. [Paper] [Website] [Code]
• "Speech World Model: Causal State-Action Planning with Explicit Reasoning for Speech", `arxiv 2025.12. [Paper]
• "Probing the effectiveness of World Models for Spatial Reasoning through Test-time Scaling", `arxiv 2025.12. [Paper] [Code]
• ProPhy: "ProPhy: Progressive Physical Alignment for Dynamic World Simulation", `arxiv 2025.12. [Paper]
• BiTAgent: "BiTAgent: A Task-Aware Modular Framework for Bidirectional Coupling between Multimodal Large Language Models and World Models", `arxiv 2025.12. [Paper]
• RELIC: "RELIC: Interactive Video World Model with Long-Horizon Memory", `arxiv 2025.12. [Paper]
• "Better World Models Can Lead to Better Post-Training Performance", `arxiv 2025.12. [Paper]
• SeeU: "SeeU: Seeing the Unseen World via 4D Dynamics-aware Generation", `arxiv 2025.12. [Paper] [Website]
• DynamicVerse: "DynamicVerse: A Physically-Aware Multimodal Framework for 4D World Modeling", `arxiv 2025.12. [Paper]
• IC-World: "IC-World: In-Context Generation for Shared World Modeling", `arxiv 2025.12. [Paper] [Code]
• WorldPack: "WorldPack: Compressed Memory Improves Spatial Consistency in Video World Modeling", `arxiv 2025.12. [Paper]
• GrndCtrl: "GrndCtrl: Grounding World Models via Self-Supervised Reward Alignment", `arxiv 2025.12. [Paper]
• ChronosObserver: "ChronosObserver: Taming 4D World with Hyperspace Diffusion Sampling", `arxiv 2025.12. [Paper]
• AVWM: "Audio-Visual World Models: Towards Multisensory Imagination in Sight and Sound", `arxiv 2025.12. [Paper]
• VCWorld: "VCWorld: A Biological World Model for Virtual Cell Simulation", `arxiv 2025.12. [Paper] [Code]
• VISTAv2: "VISTAv2: World Imagination for Indoor Vision-and-Language Navigation", `arxiv 2025.12. [Paper] [Website]
• Captain Safari: "Captain Safari: A World Engine", arxiv 2025.11. [Paper] [Website]
• WorldWander: "WorldWander: Bridging Egocentric and Exocentric Worlds in Video Generation", arxiv 2025.11. [Paper] [Code]
• Inferix: "Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation", arxiv 2025.11. [Paper] [Code]
• MagicWorld: "MagicWorld: Interactive Geometry-driven Video World Exploration", arxiv 2025.11. [Paper]
• "Counterfactual World Models via Digital Twin-conditioned Video Diffusion", arxiv 2025.11. [Paper]
• WorldGen: "WorldGen: From Text to Traversable and Interactive 3D Worlds", arxiv 2025.11. [Paper] [Website]
• X-WIN: "X-WIN: Building Chest Radiograph World Model via Predictive Sensing", arxiv 2025.11. [Paper]
• "Object-Centric World Models for Causality-Aware Reinforcement Learning", AAAI 2026. [Paper]
• "Latent-Space Autoregressive World Model for Efficient and Robust Image-Goal Navigation", arxiv 2025.11. [Paper]
• Dynamic Sparsity: "Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks", AAAI 2026. [Paper]
• MrCoM: "MrCoM: A Meta-Regularized World-Model Generalizing Across Multi-Scenarios", AAAI 2026. [Paper]
• "Next-Latent Prediction Transformers Learn Compact World Models", arxiv 2025.11. [Paper]
• DR. WELL: "DR. WELL: Dynamic Reasoning and Learning with Symbolic World Model for Embodied LLM-Based Multi-Agent Collaboration", NeurIPS 2025 Workshop: Bridging Language, Agent, and World Models for Reasoning and Planning (LAW). [Paper] [Website]
• "How Far Are Surgeons from Surgical World Models? A Pilot Study on Zero-shot Surgical Video Generation with Expert Assessment", arxiv 2025.11. [Paper]
• "From Pixels to Cooperation Multi Agent Reinforcement Learning based on Multimodal World Models", arxiv 2025.11. [Paper]
• "Bootstrap Off-policy with World Model", NIPS 2025. [Paper]
• "Clone Deterministic 3D Worlds with Geometrically-Regularized World Models", arxiv 2025.10. [Paper]
• "Semantic Communications with World Models", arxiv 2025.10. [Paper]
• TRELLISWorld: "TRELLISWorld: Training-Free World Generation from Object Generators", arxiv 2025.10. [Paper]
• WorldGrow: "WorldGrow: Generating Infinite 3D World", arxiv 2025.10. [Paper] [Code]
• PhysWorld: "PhysWorld: From Real Videos to World Models of Deformable Objects via Physics-Aware Demonstration Synthesis", arxiv 2025.10. [Paper]
• "How Hard is it to Confuse a World Model?", arxiv 2025.10. [Paper]
• "Social World Model-Augmented Mechanism Design Policy Learning", NIPS 2025. [Paper]
• VAGEN: "VAGEN: Reinforcing World Model Reasoning for Multi-Turn VLM Agents", NIPS 2025. [Paper] [Website]
• Cosmos-Surg-dVRK: "Cosmos-Surg-dVRK: World Foundation Model-based Automated Online Evaluation of Surgical Robot Policy Learning", arxiv 2025.10. [Paper]
• "Zero-shot World Models via Search in Memory", arxiv 2025.10. [Paper]
• "Vector Quantization in the Brain: Grid-like Codes in World Models", NIPS 2025. [Paper]
• Terra: "Terra: Explorable Native 3D World Model with Point Latents", arxiv 2025.10. [Paper] [Website]
• Deep SPI: "Deep SPI: Safe Policy Improvement via World Models", arxiv 2025.10. [Paper]
• "One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration", arxiv 2025.10. [Paper] [Code]
• R-WoM: "R-WoM: Retrieval-augmented World Model For Computer-use Agents", arxiv 2025.10. [Paper]
• WorldMirror: "WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting", arxiv 2025.10. [Paper]
• Unified World Models: "Unified World Models: Memory-Augmented Planning and Foresight for Visual Navigation", arxiv 2025.10. [Paper] [code]
• "Code World Models for General Game Playing", arxiv 2025.10. [Paper]
• MorphoSim: "MorphoSim: An Interactive, Controllable, and Editable Language-guided 4D World Simulator", arxiv 2025.10. [Paper] [code]
• ChronoEdit: "ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation", arxiv 2025.10. [Paper] [Website]
• SFP: "Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models", arxiv 2025.10. [Paper]
• EvoWorld: "EvoWorld: Evolving Panoramic World Generation with Explicit 3D Memory", arxiv 2025.10. [Paper] [Code]
• "World Model for AI Autonomous Navigation in Mechanical Thrombectomy", MICCAI 2025. Lecture Notes in Computer Science. [Paper]
• DyMoDreamer: "DyMoDreamer: World Modeling with Dynamic Modulation", NeurIPS 2025. [Paper] [Code]
• Dreamer4: "Training Agents Inside of Scalable World Models", arxiv 2025.09. [Paper] [Website]
• "Reinforcement Learning with Inverse Rewards for World Model Post-training", arxiv 2025.09. [Paper]
• "Context and Diversity Matter: The Emergence of In-Context Learning in World Models", arxiv 2025.09. [Paper]
• FantasyWorld: "FantasyWorld: Geometry-Consistent World Modeling via Unified Video and 3D Prediction", arxiv 2025.09. [Paper]
• "Remote Sensing-Oriented World Model", arxiv 2025.09. [Paper]
• "World Modeling with Probabilistic Structure Integration", arxiv 2025.09. [Paper]
• "One Model for All Tasks: Leveraging Efficient World Models in Multi-Task Planning", arxiv 2025.09. [Paper] [Code]
• LatticeWorld: "LatticeWorld: A Multimodal Large Language Model-Empowered Framework for Interactive Complex World Generation", arxiv 2025.09. [Paper]
• "Planning with Reasoning using Vision Language World Model", arxiv 2025.09. [Paper]
• "Social World Models", arxiv 2025.09. [Paper]
• "Dynamics-Aligned Latent Imagination in Contextual World Models for Zero-Shot Generalization", arxiv 2025.08. [Paper]
• HERO: "HERO: Hierarchical Extrapolation and Refresh for Efficient World Models", arxiv 2025.08. [Paper]
• "Scalable RF Simulation in Generative 4D Worlds", arxiv 2025.08. [Paper]
• "Finite Automata Extraction: Low-data World Model Learning as Programs from Gameplay Video", arxiv 2025.08. [Paper]
• "Visuomotor Grasping with World Models for Surgical Robots", arxiv 2025.08. [Paper]
• "In-Context Reinforcement Learning via Communicative World Models", arxiv 2025.08. [Paper] [Code]
• PIGDreamer: "PIGDreamer: Privileged Information Guided World Models for Safe Partially Observable Reinforcement Learning", ICML 2025. [Paper]
• SimuRA: "SimuRA: Towards General Goal-Oriented Agent via Simulative Reasoning Architecture with LLM-Based World Model", arxiv 2025.07. [Paper]
• "Back to the Features: DINO as a Foundation for Video World Models", arxiv 2025.07. [Paper]
• Yume: "Yume: An Interactive World Generation Model", arxiv 2025.07. [Paper] [Website] [Code]
• "LLM world models are mental: Output layer evidence of brittle world model use in LLM mechanical reasoning", arxiv 2025.07. [Paper]
• "Safety Certification in the Latent space using Control Barrier Functions and World Models", arxiv 2025.07. [Paper]
• "Assessing adaptive world models in machines with novel games", arxiv 2025.07. [Paper]
• "Graph World Model", ICML 2025. [Paper] [Website]
• MobiWorld: "MobiWorld: World Models for Mobile Wireless Network", arxiv 2025.07. [Paper]
• "Continual Reinforcement Learning by Planning with Online World Models", ICML 2025 Spotlight. [Paper]
• AirScape: "AirScape: An Aerial Generative World Model with Motion Controllability", arxiv 2025.07. [Paper] [Website]
• Geometry Forcing: "Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling", arxiv 2025.07. [Paper] [Website]
• Martian World Models: "Martian World Models: Controllable Video Synthesis with Physically Accurate 3D Reconstructions", arxiv 2025.07. [Paper] [Website]
• "What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models", ICML 2025. [Paper]
• "Critiques of World Models", arxiv 2025.07. [Paper]
• "When do World Models Successfully Learn Dynamical Systems?", arxiv 2025.07. [Paper]
• WebSynthesis: "WebSynthesis: World-Model-Guided MCTS for Efficient WebUI-Trajectory Synthesis", arxiv 2025.07. [Paper]
• "Accurate and Efficient World Modeling with Masked Latent Transformers", arxiv 2025.07. [Paper]
• Dyn-O: "Dyn-O: Building Structured World Models with Object-Centric Representations", arxiv 2025.07. [Paper]
• NavMorph: "NavMorph: A Self-Evolving World Model for Vision-and-Language Navigation in Continuous Environments", ICCV 2025. [Paper] [Code]
• "A “Good” Regulator May Provide a World Model for Intelligent Systems", arxiv 2025.06. [Paper]
• Xray2Xray: "Xray2Xray: World Model from Chest X-rays with Volumetric Context", arxiv 2025.06. [Paper]
• MATWM: "Transformer World Model for Sample Efficient Multi-Agent Reinforcement Learning", arxiv 2025.06. [Paper]
• "Measuring (a Sufficient) World Model in LLMs: A Variance Decomposition Framework", arxiv 2025.06. [Paper]
• "Efficient Generation of Diverse Cooperative Agents with World Models", arxiv 2025.06. [Paper]
• WorldLLM: "WorldLLM: Improving LLMs' world modeling using curiosity-driven theory-making", arxiv 2025.06. [Paper]
• "LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment", arxiv 2025.06. [Paper]
• "Bootstrapping World Models from Dynamics Models in Multimodal Foundation Models", arxiv 2025.06. [Paper]
• "Video World Models with Long-term Spatial Memory", arxiv 2025.06. [Paper] [Website]
• DSG-World: "DSG-World: Learning a 3D Gaussian World Model from Dual State Videos", arxiv 2025.06. [Paper]
• "Safe Planning and Policy Optimization via World Model Learning", arxiv 2025.06. [Paper]
• FOLIAGE: "FOLIAGE: Towards Physical Intelligence World Models Via Unbounded Surface Evolution", arxiv 2025.06. [Paper]
• "Linear Spatial World Models Emerge in Large Language Models", arxiv 2025.06. [Paper] [Code]
• Simple, Good, Fast: "Simple, Good, Fast: Self-Supervised World Models Free of Baggage", ICLR 2025. [Paper] [Code]
• Medical World Model: "Medical World Model: Generative Simulation of Tumor Evolution for Treatment Planning", arxiv 2025.06. [Paper]
• "General agents need world models", ICML 2025. [Paper]
• "Learning Abstract World Models with a Group-Structured Latent Space", arxiv 2025.06. [Paper]
• DeepVerse: "DeepVerse: 4D Autoregressive Video Generation as a World Model", arxiv 2025.06. [Paper]
• "World Models for Cognitive Agents: Transforming Edge Intelligence in Future Networks", arxiv 2025.06. [Paper]
• Dyna-Think: "Dyna-Think: Synergizing Reasoning, Acting, and World Model Simulation in AI Agents", arxiv 2025.06. [Paper]
• StateSpaceDiffuser: "StateSpaceDiffuser: Bringing Long Context to Diffusion World Models", arxiv 2025.05. [Paper]
• "Learning World Models for Interactive Video Generation", arxiv 2025.05. [Paper]
• "Revisiting Multi-Agent World Modeling from a Diffusion-Inspired Perspective", arxiv 2025.05. [Paper]
• "Long-Context State-Space Video World Models", arxiv 2025.05. [Paper] [Website]
• "Unlocking Smarter Device Control: Foresighted Planning with a World Model-Driven Code Execution Approach", arxiv 2025.05. [Paper]
• "World Models as Reference Trajectories for Rapid Motor Adaptation", arxiv 2025.05. [Paper]
• "Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning", arxiv 2025.05. [Paper]
• "Building spatial world models from sparse transitional episodic memories", arxiv 2025.05. [Paper]
• PoE-World: "PoE-World: Compositional World Modeling with Products of Programmatic Experts", arxiv 2025.05. [Paper] [Website]
• "Explainable Reinforcement Learning Agents Using World Models", arxiv 2025.05. [Paper]
• seq-JEPA: "seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models", arxiv 2025.05. [Paper]
• "Coupled Distributional Random Expert Distillation for World Model Online Imitation Learning", arxiv 2025.05. [Paper]
• "Learning Local Causal World Models with State Space Models and Attention", arxiv 2025.05. [Paper]
• WebEvolver: "WebEvolver: Enhancing Web Agent Self-Improvement with Coevolving World Model", arxiv 2025.04. [Paper]
• WALL-E 2.0: "WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents", arxiv 2025.04. [Paper] [Code]
• ViMo: "ViMo: A Generative Visual GUI World Model for App Agent", arxiv 2025.04. [Paper]
• "Simulating Before Planning: Constructing Intrinsic User World Model for User-Tailored Dialogue Policy Planning", SIGIR 2025. [Paper]
• CheXWorld: "CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning", CVPR 2025. [Paper] [Code]
• EchoWorld: "EchoWorld: Learning Motion-Aware World Models for Echocardiography Probe Guidance", CVPR 2025. [Paper] [Code]
• "Adapting a World Model for Trajectory Following in a 3D Game", ICLR 2025 Workshop on World Models. [Paper]
• MineWorld: "MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft", arXiv 2025.04. [Paper] [Website]
• MoSim: "Neural Motion Simulator Pushing the Limit of World Models in Reinforcement Learning", CVPR 2025. [Paper]
• "Improving World Models using Deep Supervision with Linear Probes", ICLR 2025 Workshop on World Models. [Paper]
• "Decentralized Collective World Model for Emergent Communication and Coordination", arXiv 2025.04. [Paper]
• "Adapting World Models with Latent-State Dynamics Residuals", arXiv 2025.04. [Paper]
• "Can Test-Time Scaling Improve World Foundation Model?", arXiv 2025.03. [Paper] [Code]
• "Synthesizing world models for bilevel planning", arXiv 2025.03. [Paper]
• "Long-context autoregressive video modeling with next-frame prediction", arXiv 2025.03. [Paper] [Code] [Website]
• Aether: "Aether: Geometric-Aware Unified World Modeling", arXiv 2025.03. [Paper] [Website]
• FUSDREAMER: "FUSDREAMER: Label-efficient Remote Sensing World Model for Multimodal Data Classification", arXiv 2025.03. [Paper] [Website]
• "Inter-environmental world modeling for continuous and compositional dynamics", arXiv 2025.03. [Paper]
• Disentangled World Models: "Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning", arXiv 2025.03. [Paper]
• "Revisiting the Othello World Model Hypothesis", ICLR World Models Workshop. [Paper]
• "Learning Transformer-based World Models with Contrastive Predictive Coding", arXiv 2025.03. [Paper]
• "Surgical Vision World Model", arXiv 2025.03. [Paper]
• "World Models for Anomaly Detection during Model-Based Reinforcement Learning Inference", arXiv 2025.03. [Paper]
• WMNav: "WMNav: Integrating Vision-Language Models into World Models for Object Goal Navigation", arXiv 2025.03. [Paper] [Website]
• SENSEI: "SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models", arXiv 2025.03. [Paper] [Website]
• "Learning Actionable World Models for Industrial Process Control", arXiv 2025.03. [Paper]
• "Implementing Spiking World Model with Multi-Compartment Neurons for Model-based Reinforcement Learning", arXiv 2025.03. [Paper]
• "Discrete Codebook World Models for Continuous Control", ICLR 2025. [Paper]
• Multimodal Dreaming: "Multimodal Dreaming: A Global Workspace Approach to World Model-Based Reinforcement Learning", arXiv 2025.02. [Paper]
• "Generalist World Model Pre-Training for Efficient Reinforcement Learning", arXiv 2025.02. [Paper]
• "Learning To Explore With Predictive World Model Via Self-Supervised Learning", arXiv 2025.02. [Paper]
• M^3: "M^3: A Modular World Model over Streams of Tokens", arXiv 2025.02. [Paper]
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• "Enhancing Physical Consistency in Lightweight World Models", arXiv 2025.09. [Paper]
• OccTENS: "OccTENS: 3D Occupancy World Model via Temporal Next-Scale Prediction", arXiv 2025.09. [Paper]
• IRL-VLA: "IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model", arXiv 2025.08. [Paper] [Website] [Code]
• LiDARCrafter: "LiDARCrafter: Dynamic 4D World Modeling from LiDAR Sequences", arXiv 2025.08. [Paper] [Website] [Code]
• FASTopoWM: "FASTopoWM: Fast-Slow Lane Segment Topology Reasoning with Latent World Models", arXiv 2025.07. [Paper] [Code]
• Orbis: "Orbis: Overcoming Challenges of Long-Horizon Prediction in Driving World Models", arXiv 2025.07. [Paper] [Code]
• "World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving", arXiv 2025.07. [Paper]
• NRSeg: "NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World Models", arXiv 2025.07. [Paper] [Code]
• World4Drive: "World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model", ICCV2025. [Paper] [Code]
• Epona: "Epona: Autoregressive Diffusion World Model for Autonomous Driving", ICCV2025. [Paper] [Code]
• "Towards foundational LiDAR world models with efficient latent flow matching", arXiv 2025.06. [Paper]
• SceneDiffuser++: "SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Model", CVPR 2025. [Paper]
• COME: "COME: Adding Scene-Centric Forecasting Control to Occupancy World Model", arXiv 2025.06. [Paper] [Code]
• STAGE: "STAGE: A Stream-Centric Generative World Model for Long-Horizon Driving-Scene Simulation", arXiv 2025.06. [Paper]
• ReSim: "ReSim: Reliable World Simulation for Autonomous Driving", arXiv 2025.06. [Paper] [Code] [Project Page]
• "Ego-centric Learning of Communicative World Models for Autonomous Driving", arXiv 2025.06. [Paper]
• Dreamland: "Dreamland: Controllable World Creation with Simulator and Generative Models", arXiv 2025.06. [Paper] [Project Page]
• LongDWM: "LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model", arXiv 2025.06. [Paper] [Project Page]
• GeoDrive: "GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control", arXiv 2025.05. [Paper] [Code]
• FutureSightDrive: "FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving", NeurIPS 2025. [Paper] [Code]
• Raw2Drive: "Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)", arXiv 2025.05. [Paper]
• VL-SAFE: "VL-SAFE: Vision-Language Guided Safety-Aware Reinforcement Learning with World Models for Autonomous Driving", arXiv 2025.05. [Paper] [Project Page]
• PosePilot: "PosePilot: Steering Camera Pose for Generative World Models with Self-supervised Depth", arXiv 2025.05. [Paper]
• "World Model-Based Learning for Long-Term Age of Information Minimization in Vehicular Networks", arXiv 2025.05. [Paper]
• "Learning to Drive from a World Model", arXiv 2025.04. [Paper]
• DriVerse: "DriVerse: Navigation World Model for Driving Simulation via Multimodal Trajectory Prompting and Motion Alignment", arXiv 2025.04. [Paper]
• "End-to-End Driving with Online Trajectory Evaluation via BEV World Model", arXiv 2025.04. [Paper] [Code]
• "Knowledge Graphs as World Models for Semantic Material-Aware Obstacle Handling in Autonomous Vehicles", arXiv 2025.03. [Paper]
• MiLA: "MiLA: Multi-view Intensive-fidelity Long-term Video Generation World Model for Autonomous Driving", arXiv 2025.03. [Paper] [Project Page]
• SimWorld: "SimWorld: A Unified Benchmark for Simulator-Conditioned Scene Generation via World Model", arXiv 2025.03. [Paper] [Project Page]
• UniFuture: "Seeing the Future, Perceiving the Future: A Unified Driving World Model for Future Generation and Perception", arXiv 2025.03. [Paper] [Project Page]
• EOT-WM: "Other Vehicle Trajectories Are Also Needed: A Driving World Model Unifies Ego-Other Vehicle Trajectories in Video Latent Space", arXiv 2025.03. [Paper]
• "Temporal Triplane Transformers as Occupancy World Models", arXiv 2025.03. [Paper]
• InDRiVE: "InDRiVE: Intrinsic Disagreement based Reinforcement for Vehicle Exploration through Curiosity Driven Generalized World Model", arXiv 2025.02. [Paper]
• MaskGWM: "MaskGWM: A Generalizable Driving World Model with Video Mask Reconstruction", arXiv 2025.02. [Paper]
• Dream to Drive: "Dream to Drive: Model-Based Vehicle Control Using Analytic World Models", arXiv 2025.02. [Paper]
• "Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving", ICLR 2025. [Paper]
• "Dream to Drive with Predictive Individual World Model", IEEE TIV. [Paper] [Code]
• HERMES: "HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation", arXiv 2025.01. [Paper]
• AdaWM: "AdaWM: Adaptive World Model based Planning for Autonomous Driving", ICLR 2025. [Paper]
• AD-L-JEPA: "AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR Data", arXiv 2025.01. [Paper]
• DrivingWorld: "DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT", arXiv 2024.12. [Paper] [Code] [Project Page]
• DrivingGPT: "DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers", arXiv 2024.12. [Paper] [Project Page]
• "An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training", arXiv 2024.12. [Paper]
• GEM: "GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control", arXiv 2024.12. [Paper] [Project Page]
• GaussianWorld: "GaussianWorld: Gaussian World Model for Streaming 3D Occupancy Prediction", arXiv 2024.12. [Paper] [Code]
• Doe-1: "Doe-1: Closed-Loop Autonomous Driving with Large World Model", arXiv 2024.12. [Paper] [Project Page] [Code]
• "Pysical Informed Driving World Model", arXiv 2024.12. [Paper] [Project Page]
• InfiniCube: "InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models", arXiv 2024.12. [Paper] [Project Page]
• InfinityDrive: "InfinityDrive: Breaking Time Limits in Driving World Models", arXiv 2024.12. [Paper] [Project Page]
• ReconDreamer: "ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration", arXiv 2024.11. [Paper] [Project Page]
• Imagine-2-Drive: "Imagine-2-Drive: High-Fidelity World Modeling in CARLA for Autonomous Vehicles", ICRA 2025. [Paper] [Project Page]
• DynamicCity: "DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes", ICLR 2025 Spotlight. [Paper] [Project Page] [Code]
• DriveDreamer4D: "World Models Are Effective Data Machines for 4D Driving Scene Representation", arXiv 2024.10. [Paper] [Project Page]
• DOME: "Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model", arXiv 2024.10. [Paper] [Project Page]
• SSR: "Does End-to-End Autonomous Driving Really Need Perception Tasks?", arXiv 2024.09. [Paper] [Code]
• "Mitigating Covariate Shift in Imitation Learning for Autonomous Vehicles Using Latent Space Generative World Models", arXiv 2024.09. [Paper]
• LatentDriver: "Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Driving", arXiv 2024.09. [Paper] [Code]
• RenderWorld: "World Model with Self-Supervised 3D Label", arXiv 2024.09. [Paper]
• OccLLaMA: "An Occupancy-Language-Action Generative World Model for Autonomous Driving", arXiv 2024.09. [Paper]
• DriveGenVLM: "Real-world Video Generation for Vision Language Model based Autonomous Driving", arXiv 2024.08. [Paper]
• Drive-OccWorld: "Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving", arXiv 2024.08. [Paper]
• CarFormer: "Self-Driving with Learned Object-Centric Representations", ECCV 2024. [Paper] [Code]
• BEVWorld: "A Multimodal World Model for Autonomous Driving via Unified BEV Latent Space", arXiv 2024.07. [Paper] [Code]
• TOKEN: "Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving", arXiv 2024.07. [Paper]
• UMAD: "Unsupervised Mask-Level Anomaly Detection for Autonomous Driving", arXiv 2024.06. [Paper]
• SimGen: "Simulator-conditioned Driving Scene Generation", arXiv 2024.06. [Paper] [Code]
• AdaptiveDriver: "Planning with Adaptive World Models for Autonomous Driving", arXiv 2024.06. [Paper] [Code]
• UnO: "Unsupervised Occupancy Fields for Perception and Forecasting", CVPR 2024. [Paper] [Code]
• LAW: "Enhancing End-to-End Autonomous Driving with Latent World Model", arXiv 2024.06. [Paper] [Code]
• Delphi: "Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation", arXiv 2024.06. [Paper] [Code]
• OccSora: "4D Occupancy Generation Models as World Simulators for Autonomous Driving", arXiv 2024.05. [Paper] [Code]
• MagicDrive3D: "Controllable 3D Generation for Any-View Rendering in Street Scenes", arXiv 2024.05. [Paper] [Code]
• Vista: "A Generalizable Driving World Model with High Fidelity and Versatile Controllability", NeurIPS 2024. [Paper] [Code]
• CarDreamer: "Open-Source Learning Platform for World Model based Autonomous Driving", arXiv 2024.05. [Paper] [Code]
• DriveSim: "Probing Multimodal LLMs as World Models for Driving", arXiv 2024.05. [Paper] [Code]
• DriveWorld: "4D Pre-trained Scene Understanding via World Models for Autonomous Driving", CVPR 2024. [Paper]
• LidarDM: "Generative LiDAR Simulation in a Generated World", arXiv 2024.04. [Paper] [Code]
• SubjectDrive: "Scaling Generative Data in Autonomous Driving via Subject Control", arXiv 2024.03. [Paper] [Project]
• DriveDreamer-2: "LLM-Enhanced World Models for Diverse Driving Video Generation", arXiv 2024.03. [Paper] [Code]
• Think2Drive: "Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving", ECCV 2024. [Paper]
• MARL-CCE: "Modelling Competitive Behaviors in Autonomous Driving Under Generative World Model", ECCV 2024. [Paper] [Code]
• GenAD: "Generalized Predictive Model for Autonomous Driving", CVPR 2024. [Paper] [Data]
• GenAD: "Generative End-to-End Autonomous Driving", ECCV 2024. [Paper] [Code]
• NeMo: "Neural Volumetric World Models for Autonomous Driving", ECCV 2024. [Paper]
• MARL-CCE: "Modelling-Competitive-Behaviors-in-Autonomous-Driving-Under-Generative-World-Model", ECCV 2024. [Code]
• ViDAR: "Visual Point Cloud Forecasting enables Scalable Autonomous Driving", CVPR 2024. [Paper] [Code]
• Drive-WM: "Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving", CVPR 2024. [Paper] [Code]
• Cam4DOCC: "Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications", CVPR 2024. [Paper] [Code]
• Panacea: "Panoramic and Controllable Video Generation for Autonomous Driving", CVPR 2024. [Paper] [Code]
• OccWorld: "Learning a 3D Occupancy World Model for Autonomous Driving", ECCV 2024. [Paper] [Code]
• Copilot4D: "Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion", ICLR 2024. [Paper]
• DrivingDiffusion: "Layout-Guided multi-view driving scene video generation with latent diffusion model", ECCV 2024. [Paper] [Code]
• SafeDreamer: "Safe Reinforcement Learning with World Models", ICLR 2024. [Paper] [Code]
• MagicDrive: "Street View Generation with Diverse 3D Geometry Control", ICLR 2024. [Paper] [Code]
• DriveDreamer: "Towards Real-world-driven World Models for Autonomous Driving", ECCV 2024. [Paper] [Code]
• SEM2: "Enhance Sample Efficiency and Robustness of End-to-end Urban Autonomous Driving via Semantic Masked World Model", TITS. [Paper]

If you find this repository useful, please consider citing this list:

@misc{leo2024worldmodelspaperslist,
    title = {Awesome-World-Models},
    author = {Leo Fan},
    journal = {GitHub repository},
    url = {https://github.com/leofan90/Awesome-World-Models},
    year = {2024},
}