The Human Creativity Benchmark
Modern AI evaluation frameworks treat evaluator disagreement as noise to be resolved. In creative domains, professional disagreement reflects genuine differences in taste, not measurement error. We argue that evaluating creative AI requires preserving two distinct signals: convergence, where professionals align around shared best practices, and divergence, where individual taste legitimately varies. We present the Human Creativity Benchmark (HCB), a benchmark that operationalizes this separation by collecting pairwise preferences, scalar ratings on prompt adherence, usability, and visual appea
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- LinkedLinked via unknownWhy Aren’t We Measuring How AI Affects Humans? →
- LinkedLinked via unknownFabiojvv/ai-cortex-hub →
- PossiblePossibly related (embedding) · 52%By modeling visual saliency, AI improves ratings of artistic product designs - Tech Xplore →
- FuzzySimilar title/name (fuzzy) · 59%jeinlee1991/chinese-llm-benchmark →
“Fuzzy title match (0.73): “The Human Creativity Benchmark” ≈ “jeinlee1991/chinese-llm-benchmark””
- PossiblePossibly related (embedding) · 49%Sharing your ideas to ai →
