Text conditioning scaling paper adds structured prompts to improve visual generation
shangbinfeng · x · 2026-08-04
- The paper studies how text conditioning scales in visual generation and finds that longer prompts alone do not reliably add useful supervision.
- It introduces two measures, GPG and ED, to quantify structured caption information and shows converged diffusion loss tracks structured language.
- The authors split generation quality into diffusability and promptability, then improve both with structured prompts and a trained prompter.
- The resulting system reportedly beats open-weight models on most compositional, reasoning, and world-knowledge benchmarks, and matches or surpasses closed models on many evaluations.
Related event: Structured Prompts Follow Linear Scaling Law in Visual Generation(2 posts)→
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