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The Cosine Schedule is Fisher-Rao-Optimal for Masked Discrete Diffusion Models

Machine Learning 2025-10-07 v2 Machine Learning

Abstract

In this work, we study the problem of choosing the discretisation schedule for sampling from masked discrete diffusion models in terms of the information geometry of the induced probability path. Specifically, we show that the optimal schedule under the Fisher-Rao geometry recovers the popularly-used cosine schedule.

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Cite

@article{arxiv.2508.04884,
  title  = {The Cosine Schedule is Fisher-Rao-Optimal for Masked Discrete Diffusion Models},
  author = {Leo Zhang and Saifuddin Syed},
  journal= {arXiv preprint arXiv:2508.04884},
  year   = {2025}
}

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