SOURCE-LINKED INTELLIGENCE
Blending Concepts: Benchmarking Visual Metaphor Generation in Text-to-Image Models
Text-to-image (T2I) models have achieved remarkable success at faithfully rendering specified objects and attributes, yet their ability to produce visual metaphors, images that convey abstract ideas by combining elements from two distinct domains, remains largely unexamined. To bridge this gap, we introduce VMetaphor-Bench, the first benchmark for evaluating visual metaphor generation in T2I models. It comprises 1,500 visual metaphors curated from real-world creative imagery, organized into three levels and ten categories, with each sample paired with two prompts of differing specificity. For
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T12:07:39.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.