Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A Curated List of Awesome Video World Models with AR Diffusion: Covering Algorithms, Applications, and Infrastructure, Aimed at Serving as a Comprehensive Resource for Researchers, Practitioners, and Enthusiasts.
| Date | Stars |
|---|---|
| 2026-07-24 | 670 |
| 2026-07-25 | 673 |
| 2026-07-28 | 676 |
| 2026-07-30 | 676 |
| 2026-08-06 | 676 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<div align="center"> # 📹 Awesome Video World Models with AR Diffusion [](https://github.com/gracezhao1997/Awesome-Video-World-Models-with-AR-Diffusion)  [](assets/wechat.jpg) </div> ## Overview This repository focuses on **Video World Models with Autoregressive (AR) Diffusion**, a promising paradigm for **scalable, consistent and interactive world modeling** (e.g., Genie 3). It aims to serve as a comprehensive and structured resource for researchers, practitioners, and enthusiasts interested in AR diffusion-based video world modeling. To stay at the forefront of the field, **this repository is updated weekly**. ### 🔥NEW: minWM: Full-Stack Open-Source Video World Model Data & Traing & Distillation & Inference Framework Try our [minWM](https://github.com/shengshu-ai/minWM), the first full-stack open-source framework that walks you end-to-end through turning a bidirectional T2V foundation model into an action-conditioned video world model — with **example data, runnable scripts, Claude skills capturing our hands-on experience, and onboarding knowledge for newcomers**! []([https://github.com/kwsong0113/diffusion-forcing-transformer](https://github.com/shengshu-ai/minWM)) <a href="https://arxiv.org/abs/2605.30263"><img src="https://img.shields.io/badge/Technical_Report-arXiv-b31b1b?logo=arxiv&logoColor=white" alt="Technical Report"></a> <a href="https://huggingface.co/MIN-Lab/minWM"><img src="https://img.shields.io/badge/Hugging_Face-Models-FFD21E?logo=huggingface&logoColor=black" alt="Hugging Face"></a> ### 🌟 Key Features * **[Structured Taxonomy](#table-of-contents):** We organize the evolving ecosystem from three complementary perspectives: **Algorithmic Foundations**, **Real-world Applications**, and **Infrastructure-level Acceleration**. Together, these dimensions reflect the full stack of AR diffusion—from modeling design to real-time interactive deployment. * **[One-Stop Citation Collection](./video-world-models.bib):** 📚 We provide a [**consolidated BibTeX file**](./video-world-models.bib) containing all papers listed in this repository. You can easily import it into your LaTeX or Zotero projects with one click! ### 📬 Contact This repository is curated and maintained by: * [**Min Zhao**](https://gracezhao1997.github.io/) ([[email protected]](mailto:[email protected])) * [**Hongzhou Zhu**](https://zhuhz22.github.io/) ([[email protected]](mailto:[email protected])) * [**Wenqiang Sun**](https://scholar.google.com/citations?user=XEUeiTEAAAAJ&hl=en) ([[email protected]](mailto:[email protected])) * [**Bokai Yan**](https://github.com/KasenYoung) ([[email protected]](mailto:[email protected])) For any questions or suggestions, please feel free to reach out to us. * 🎯 We have not yet compiled an exhaustive list of all related work. We apologize for any omissions and **welcome pull requests to merge them in**. * 💡 We also welcome high-level categorization, synthesis, and perspective contributions to improve the organization and clarity of this repository. ## Table of Contents - [1. Algorithm](#1-algorithm) - [1.1 AR Diffusion (native pretraining)](#11-ar-diffusion-native-pretraining) - [1.2 AR Diffusion Distillation for Real-time Generation (post training)](#12--ar-diffusion-distillation-for-real-time-generation-post-training) - [1.3 Long Video Generation](#13-long-video-generation) - [2. Application](#2-application) - [2.1 Open-source AR Video Foundation Models](#21-open-source-ar-video-foundation-models) - [2.2 Interactive Video Action World Model](#22-interactive-video-action-world-model) - [
Excerpt of 66,735 characters
Read on GitHub
Hongzhou Zhu · Tsinghua University
120
China
35
6
6
4
2
2
Shenghai Yuan · PKU-YuanGroup · China
1
1
Zhicheng Sun · Peking University
1
1
1
1
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:39dd6bdbd4ebf320, topic:awesome-list, desc:curated list
matched fp:39dd6bdbd4ebf320, topic:computer-vision
matched fp:39dd6bdbd4ebf320, topic:diffusion-models
matched fp:39dd6bdbd4ebf320, topic:video-generation, readme:video generation