Text-to-image models excel at natural image synthesis but struggle with graphic design, where success depends on satisfying precise constraints on typography, layout, color, and visual communication. While prompt optimization offers an attractive alternative to expensive diffusion model fine-tuning, learning prompts fo...
Adrienne Deganutti, Purvanshi Mehta, Simon Hadfield et al.· 0 citations
A criterion-agnostic signal-validation framework based on Kendall's $\tau$, majority-vote probability, and Condorcet cycles against exact iid-uniform nulls; the analysis reveals significant but moderate designer agreement, with every TASTE criterion rejecting the random-rater null.
Hao-Nan Zhu, Elad Hirsch, A. Minetti et al.· arXiv.org· 0 citations
A typography-focused benchmark of 12 tasks grounded in a layered-composition corpus of 989 real-world design templates and 2,568 text elements is introduced to quantify how well future design partners can perceive, reproduce, and manipulate the ty-pographic layer designers care about most.
Jaejung Seol, Elad Hirsch, Hao-Nan Zhu et al.· 0 citations
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