Nano World Models: A Minimalist Implementation of Future Video Prediction
World models have become a central paradigm for learning predictive simulators that support generation, planning, and decision-making. Yet, despite rapid progress in industry-scale interactive video generation, the broader research community still lacks compact, reproducible, and easily extensible implementations for studying the design choices underlying modern world models. We introduce Nano World Models, a minimalist codebase for future video prediction centered around diffusion forcing. Nano World Models provides a unified interface for generative objectives, model scales, action-conditioning mechanisms, latent observation spaces, datasets, evaluation protocols, and long-horizon rollo...
| Authors | Siqiao Huang, Partha Kaushik, Michael Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 17 May 2026 |
| Last updated at source | 27 May 2026 |
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