TASTE: A Designer-Annotated Multi-Dimensional Preference Dataset for AI-Generated Graphic Design
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.