π minWM: The First Full-Stack Open-Source World Model Framework
9
41 commits
2 linked in READMEs
updated Sep 10, 2026
A full-stack framework and tutorial for newcomers, rather than a specific model.
minWM is our contribution to the world-model community: a 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 β with example data, runnable scripts, Claude skills capturing our hands-on experience, and onboarding knowledge for newcomers. We hope more researchers and developers join us in growing the community together.
If you find this work useful, please cite:
@article{zhu2026causal,
title={Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation},
author={Zhu, Hongzhou and Zhao, Min and He, Guande heg and Su, Hang and Li, Chongxuan and Zhu, Jun},
journal={arXiv preprint arXiv:2602.02214},
year={2026}
}
@article{zhao2026causal,
title={Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation},
author={Zhao, Min and Zhu, Hongzhou and Zheng, Kaiwen and Zhou, Zihan and Yan, Bokai and Li, Xinyuan and Yang, Xiao and Li, Chongxuan and Zhu, Jun},
journal={arXiv preprint arXiv:2605.15141},
year={2026}
}
π minWM: The First Full-Stack Open-Source World Model Framework
9
41 commits
2 linked in READMEs
updated Sep 10, 2026
A full-stack framework and tutorial for newcomers, rather than a specific model.
minWM is our contribution to the world-model community: a 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 β with example data, runnable scripts, Claude skills capturing our hands-on experience, and onboarding knowledge for newcomers. We hope more researchers and developers join us in growing the community together.
If you find this work useful, please cite:
@article{zhu2026causal,
title={Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation},
author={Zhu, Hongzhou and Zhao, Min and He, Guande heg and Su, Hang and Li, Chongxuan and Zhu, Jun},
journal={arXiv preprint arXiv:2602.02214},
year={2026}
}
@article{zhao2026causal,
title={Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation},
author={Zhao, Min and Zhu, Hongzhou and Zheng, Kaiwen and Zhou, Zihan and Yan, Bokai and Li, Xinyuan and Yang, Xiao and Li, Chongxuan and Zhu, Jun},
journal={arXiv preprint arXiv:2605.15141},
year={2026}
}