xzxxntxdy/History-Forcing-Data

History Forcing: Distilling History-Dependent Continuations for Long-Horizon Video World Models

Hangyi Kuang^1,*, Chengzhi Wang^1,*, Yefei He¹, Weijie Wang¹, Yuke Zhao^1,2, Zhuokun Chen³
Zisu Huang², Yifan Yang², Xiaoxuan He^1,†, Feng Chen^4,†, Bohan Zhuang¹

¹ Zhejiang University   ² Microsoft Research   ³ Monash University   ⁴ Adelaide University
^* Equal contribution   ^† Corresponding authors

Paper · Project · Code · Models · Dataset

Data for the out-of-sight world-modeling application of History Forcing. Fixed-camera teacher rollouts provide evolving scene history that guides the student’s continuation when its camera returns.

The repository provides training inputs and evaluation data:

• Training: 200 initial scene images from Pexels, each paired with four camera trajectories, yielding 800 training samples.
• PlayWorld Out-of-sight: 43 evaluation inputs with camera trajectories.
• MemoBench Real: 164 evaluation inputs with camera trajectories and reference videos.

Images and prompts are included in the Parquet files. Loading and evaluation are provided in the code.

Sources: Pexels, PlayWorld, and MemoBench.

News

• 2026-11-03: Our paper is now available on arXiv.

Citation

@article{kuang2026historyforcing,
  title={History Forcing: Distilling History-Dependent Continuations for Long-Horizon Video World Models},
  author={Kuang, Hangyi and Wang, Chengzhi and He, Yefei and Wang, Weijie and Zhao, Yuke and Chen, Zhuokun and Huang, Zisu and Yang, Yifan and He, Xiaoxuan and Chen, Feng and Zhuang, Bohan},
  journal={arXiv preprint arXiv:2611.02782},
  year={2026}
}