arXiv Artificial Intelligence

The Golden Path Hypothesis: Reusable Schedules in Diffusion Caching

1 hour ago 01.10.2026 07:00 👁 1 views
The Golden Path Hypothesis: Reusable Schedules in Diffusion Caching

Quick summary

arXiv:2609.39343v1 Announce Type: new Abstract: Diffusion caching accelerates generation by replacing transformer computation with cached or predicted features at selected denoising steps. We introduce the Golden Path Hypothesis (GPH): under fixed inference conditions, prompt-independent cache schedules can achieve final-output quality comparable to the best prompt-specific schedules across prompts. We investigate the GPH across ten caching methods, four image and video models, and three cache ratios. Prompt-adaptive methods repeatedly select a small number of schedules, and reusing their most

Key takeaways

  • arXiv:2609.39343v1 Announce Type: new Abstract: Diffusion caching accelerates generation by replacing transformer computation with cached or predicted features at selected denoising steps.
  • We introduce the Golden Path Hypothesis (GPH): under fixed inference conditions, prompt-independent cache schedules can achieve final-output quality comparable to the best prompt-specific schedules across prompts.
  • We investigate the GPH across ten caching methods, four image and video models, and three cache ratios.

Why it matters

The importance of “The Golden Path Hypothesis: Reusable Schedules in Diffusion Caching” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗