Foundation paper of World Model

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

Blog or Technical Report

• NVIDIA OmniDreams, NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation. [Paper]
• Cosmos 3, Cosmos 3: Omnimodal World Models for Physical AI. [Paper] [Website]
• X Square Robot, WALL-WM: Carving World Action Modeling at the Event Joints. [Paper] [Website]
• GE-Sim 2.0, GE-Sim 2.0: A Roadmap Towards Comprehensive Closed-loop Video World Simulators for Robotic Manipulation. [Paper] [Website]
• Xiaomi EV World Model, Xiaomi EV World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving. [Paper] [Website]
• Coowa, The DAWN of World-Action Interactive Models. [Paper]
• Being-H0.7, Being-H0.7: A Latent World-Action Model from Egocentric Videos. [Paper]
• MotuBrain, MotuBrain: An Advanced World Action Model for Robot Control. [Paper]
• Cortex 2.0, Cortex 2.0: Grounding World Models in Real-World Industrial Deployment. [Paper]
• HY-World 2.0, HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D World. [Paper] [Website] [Code]
• Helios, Real Real-Time Long Video Generation Model. [Paper] [Website] [Code]
• Seedance 2.0, Seedance 2.0: Advancing Video Generation for World Complexity. [Paper] [Website]
• Matrix-Game 3.0, Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory. [Paper] [Website]
• HY-Embodied-0.5, HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents. [Paper] [Website]
• OpenWorldLib, OpenWorldLib: A Unified Codebase and Definition of Advanced World Models. [Paper]
• ABot-PhysWorld, ABot-PhysWorld: Interactive World Foundation Model for Robotic Manipulation with Physics Alignment. [Paper]
• GigaWorld-Policy, GigaWorld-Policy: An Efficient Action-Centered World--Action Model. [Paper]
• GigaBrain-0.5M*, GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning. [Paper] [Website]
• ALIVE, ALIVE: Animate Your World with Lifelike Audio-Video Generation. [Paper] [Website]
• DreamDojo, DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos. [Paper] [Website]
• lingbot-va, Causal World Modeling for Robot Control. [Paper] [Website] [Code]
• lingbot-world, Advancing Open-source World Models. [Paper] [Website] [Code]
• TARS, World In Your Hands: A Large-Scale and Open-source Ecosystem for Learning Human-centric Manipulation in the Wild. [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]

Survey

• "From World Action Models to Embodied Brains: A Roadmap for Open-World Physical Intelligence", arxiv 2026.07. [Paper]
• "From World Models to World Action Models: A Concise Tutorial for Robotics", arxiv 2026.07. [Paper]
• "Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models", arxiv 2026.06. [Paper]
• "Medical world models: representing medical states, modelling clinical dynamics and guiding intervention policies", arxiv 2026.06. [Paper]
• "Bridging the Agent-World Gap: Text World Models for LLM-based Agents", arxiv 2026.06. [Paper]
• "Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends", arxiv 2026.05. [Paper]
• "Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses" arXiv 2026.05. [Paper] [Website]
• "Why We Need World Models for AGI: Where LLMs Fail and How World Models May Outperform" arXiv 2026.05. [Paper]
• "World Actio