https://github.com/nik-55/world-models

A curated list of research and projects on world models
https://github.com/nik-55/world-models

curated-list physical-ai spatial-intelligence world-models

Last synced: 15 days ago
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A curated list of research and projects on world models

• Host: GitHub
• URL: https://github.com/nik-55/world-models
• Owner: nik-55
• License: cc0-1.0
• Created: 2025-10-03T06:19:50.000Z (5 months ago)
• Default Branch: master
• Last Pushed: 2026-02-07T07:26:17.000Z (about 1 month ago)
• Last Synced: 2026-02-07T17:36:44.628Z (about 1 month ago)
• Topics: curated-list, physical-ai, spatial-intelligence, world-models
• Homepage:
• Size: 108 KB
• Stars: 5
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
A world model is a deep neural network system that learns to internally represent and simulate how the world works including its physical dynamics, objects, agents, and causal relationships so that it can predict how environments evolve and how actions will affect them. Instead of passively recognizing patterns, a world model builds an active understanding of change, enabling it to generate, imagine, and interact with coherent virtual worlds over time.

Checkout the following resources that maintain more exhaustive list on world models research:

- [LMD0311/Awesome-World-Model](https://github.com/LMD0311/Awesome-World-Model)

- [leofan90/Awesome-World-Models](https://github.com/leofan90/Awesome-World-Models)

- [knightnemo/Awesome-World-Models](https://github.com/knightnemo/Awesome-World-Models)

- [Li-Zn-H/AwesomeWorldModels](https://github.com/Li-Zn-H/AwesomeWorldModels)

- [gracezhao1997/Awesome-Video-World-Models-with-AR-Diffusion](https://github.com/gracezhao1997/Awesome-Video-World-Models-with-AR-Diffusion)

[@bilawalsidhu](https://www.youtube.com/@bilawalsidhu)'s YouTube channel covers a lot about the landscape of world models and how technology is evolving.

The following is a curated list of research, projects, and works related to the development of world models.

| Title | Date | Links |

| :--- | :--- | :--- |

| Self-Improving World Modelling with Latent Actions | 15th Feb 2026 | [arXiv](https://arxiv.org/pdf/2602.06130)
[Github](https://github.com/yfqiu-nlp/swirl) |

| Waymo World Model (Built on Genie 3) | 6th Feb 2026 | [Blog](https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simulation) |

| Infinite-World: Scaling Interactive World Models to 1000-Frame Horizons via Pose-Free Hierarchical Memory | 3rd Feb 2026 | [arXiv](https://arxiv.org/pdf/2602.02393)
[Github](https://github.com/MeiGen-AI/Infinite-World) |

| Advancing Open-source World Models | 28th Jan 2026 | [arXiv](https://arxiv.org/pdf/2601.20540)
[Github](https://github.com/Robbyant/lingbot-world) |

| Astra : General Interactive World Model With Autoregressive Denoising | 27th Jan 2026 | [arXiv](https://arxiv.org/pdf/2512.08931)
[Github](https://github.com/EternalEvan/Astra) |

| HY-World 1.5: A Systematic Framework for Interactive World Modeling with Real-Time Latency and Geometric Consistency | 17th December 2025 | [arXiv](https://arxiv.org/pdf/2512.14614)
[Github](https://github.com/Tencent-Hunyuan/HY-WorldPlay) |

| SimWorld: An Open-ended Realistic Simulator for Autonomous Agents in Physical and Social Worlds | Around December 2025 | [Report](https://simworld.org/assets/white_paper.pdf)
[Github](https://github.com/SimWorld-AI/SimWorld) |

| World Models That Know When They Don’t Know: Controllable Video Generation with Calibrated Uncertainty | 5th December 2025 | [arXiv](https://arxiv.org/pdf/2512.05927)
[Github](https://github.com/irom-princeton/c-cubed) |

| WorldScore: A Unified Evaluation Benchmark for World Generation | 29th Nov 2025 | [arXiv](https://arxiv.org/pdf/2504.00983) |

| Infinity-RoPE: Action-Controllable Infinite Video Generation Emerges From Autoregressive Self-Rollout | 25th Nov 2025 | [arXiv](https://arxiv.org/pdf/2511.20649)
[Blog](https://infinity-rope.github.io/#) |

| GigaWorld-0: World Models as Data Engine to Empower Embodied AI | 25th Nov 2025 | [arXiv](https://arxiv.org/pdf/2511.19861) |

| RynnVLA-002: A Unified Vision-Language-Action and World Model | 21st Nov 2025 | [arXiv](https://arxiv.org/pdf/2511.17502)
[Github](https://github.com/alibaba-damo-academy/RynnVLA-002) |

| PAN: A World Model for General, Interactable, and Long-Horizon World Simulation | 13th Nov 2025 | [arXiv](https://arxiv.org/pdf/2511.09057) |

| SIMA 2: An Agent that Plays, Reasons, and Learns With You in Virtual 3D Worlds | 13th Nov 2025 | [Blog](https://deepmind.google/blog/sima-2-an-agent-that-plays-reasons-and-learns-with-you-in-virtual-3d-worlds/)
[Report](https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/sima-2-an-agent-that-plays-reasons-and-learns-with-you-in-virtual-3d-worlds/SIMA_Tech_Report_2025.pdf) |

| Marble: A Multimodal World Model | 12th Nov 2025 | [Blog](https://www.worldlabs.ai/blog/marble-world-model) |

| Robot Learning from a Physical World Model | 10th Nov 2025 | [arXiv](https://arxiv.org/pdf/2511.07416)
[Github](https://pointscoder.github.io/PhysWorld_Web/) |

| Emu3.5: Native Multimodal Models are World Learners | 30th Oct 2025 | [Report](https://emu.world/Emu35_tech_report.pdf)
[Github](https://github.com/baaivision/Emu3.5) |

| RLVR-World: Training World Models with Reinforcement Learning | 25th Oct 2025 | [arXiv](https://arxiv.org/pdf/2505.13934)
[Github](https://github.com/thuml/RLVR-World) |

| World-in-World: World Models in a Closed-Loop World | 20th Oct 2025 | [arXiv](https://arxiv.org/pdf/2510.18135)
[Github](https://github.com/World-In-World/world-in-world) |

| CTRL-WORLD: A CONTROLLABLE GENERATIVE WORLD MODEL FOR ROBOT MANIPULATION | 15th Oct 2025 | [arXiv](https://arxiv.org/pdf/2510.10125)
[Github](https://github.com/Robert-gyj/Ctrl-World) |

| WORLDGYM: WORLD MODEL AS AN ENVIRONMENT FOR POLICY EVALUATION | 30th Sep 2025 | [arXiv](https://arxiv.org/pdf/2506.00613)
[Github](https://github.com/world-model-eval/world-model-eval) |

| Training Agents Inside of Scalable World Models | 29th Sep 2025 | [arXiv](https://arxiv.org/pdf/2509.24527)
[Blog](https://danijar.com/project/dreamer4/) |

| Video models are zero-shot learners and reasoners | 29th Sep 2025 | [arXiv](https://arxiv.org/pdf/2509.20328)
[Blog Post](https://video-zero-shot.github.io/) |

| CAN AI PERCEIVE PHYSICAL DANGER AND INTERVENE? | 23rd Sep 2025 | [arXiv](https://arxiv.org/pdf/2509.21651)
[Blog](https://asimov-benchmark.github.io/v2/) |

| **Matrix-Game 2.0**: An Open-Source, Real-Time, and Streaming Interactive World Model | 18 August 2025 | [arXiv](https://arxiv.org/pdf/2508.13009)
[GitHub](https://github.com/SkyworkAI/Matrix-Game/tree/main/Matrix-Game-2) |

| **Genie 3**: A new frontier for world models | 5 August 2025 | [Blog Post](https://deepmind.google/discover/blog/genie-3-a-new-frontier-for-world-models/) |

| **YUME**: An Interactive World Generation Model | 23 July 2025 | [arXiv](https://arxiv.org/pdf/2507.17744)
[GitHub](https://github.com/stdstu12/YUME) |

| **Cosmos**: World Foundation Model Platform for Physical AI | 9 July 2025 | [arXiv](https://arxiv.org/pdf/2501.03575) |

| **Matrix-Game**: Interactive World Foundation Model | 23 June 2025 | [arXiv](https://arxiv.org/pdf/2506.18701) |

| **Hunyuan-GameCraft**: High-dynamic Interactive Game Video Generation with Hybrid History Condition | 20 June 2025 | [Project Page](https://hunyuan-gamecraft.github.io/)
[arXiv](https://arxiv.org/pdf/2506.17201) |

| **V-JEPA 2**: Self-Supervised Video Models Enable Understanding, Prediction and Planning | 11 June 2025 | [arXiv](https://arxiv.org/pdf/2506.09985)
[Blog Post](https://ai.meta.com/vjepa/) |

| **Long-Context State-Space Video World Models** | 26 May 2025 | [arXiv](https://arxiv.org/pdf/2505.20171) |

| Do generative video models understand physical principles? | 27th February 2025 | [arXiv](https://arxiv.org/pdf/2501.09038) |

| **Genie 2**: A large-scale foundation world model | 4 December 2024 | [Blog Post](https://deepmind.google/discover/blog/genie-2-a-large-scale-foundation-world-model/) |

| **Oasis**: A Universe in a Transformer | 31 October 2024 | [Project Page](https://oasis-model.github.io/)
[GitHub](https://github.com/etched-ai/open-oasis) |

| **Diffusion for World Modeling**: Visual Details Matter in Atari | 30 October 2024 | [arXiv](https://arxiv.org/pdf/2405.12399) |

| A generalist AI agent for 3D virtual environments (**SIMA**) | 13 March 2024 | [Blog Post](https://deepmind.google/discover/blog/sima-generalist-ai-agent-for-3d-virtual-environments/)
[arXiv](https://arxiv.org/pdf/2404.10179) |

| **Genie**: Generative Interactive Environments | 23 February 2024 | [Publication](https://deepmind.google/research/publications/60474/)
[arXiv](https://arxiv.org/pdf/2402.15391) |

| Video generation models as world simulators (**Sora**) | 15 February 2024 | [Blog Post](https://openai.com/index/video-generation-models-as-world-simulators/) |

Also checkout Magica 2 by [Dynamics lab](https://blog.dynamicslab.ai/).  It is similar to Genie 3, however unable to find much more information.

The following are organizations actively involved in the development of world models

- [Google DeepMind](https://deepmind.google/discover/blog/genie-3-a-new-frontier-for-world-models/)

- [SkyworkAI](https://github.com/SkyworkAI/Matrix-Game)

- [Hunyuan](https://hunyuan-gamecraft.github.io/)

- [Nvidia](https://github.com/nvidia-cosmos)

- [Worldlabs.AI](https://www.worldlabs.ai/)

- [SPAITIAL](https://www.spaitial.ai/)

- [Runway](https://runwayml.com/)

- [Odyssey](https://odyssey.ml/)

- [Luma Labs](https://lumalabs.ai/)

Talks, Blogs & Podcasts

- [Jim Fan on Nvidia's Roadmap for Embodied AI](https://youtu.be/_2NijXqBESI?si=Kg0xZbLBts_VKUkT)

- [From Words to Worlds: Spatial Intelligence is AI’s Next Frontier](https://drfeifei.substack.com/p/from-words-to-worlds-spatial-intelligence)

- [What is world model? (Deepmind)](https://blog.google/company-news/inside-google/googlers/ask-a-techspert/what-is-a-world-model-project-genie/)

Feel free to open a PR and contribute!  

Join the discussion at [r/world_model](https://www.reddit.com/r/world_model/) on Reddit.