AI RESEARCH
WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation
arXiv CS.CL
•
ArXi:2503.07265v4 Announce Type: replace-cross Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evaluation standards predominantly focus on image realism and shallow text-image alignment, lacking a comprehensive assessment of complex semantic understanding and world knowledge integration in text-to-image generation. To address this challenge, we propose \textbf{WISE}, the first benchmark specifically designed for \textbf{W}orld Knowledge-\textbf{I}nformed \textbf{S}emantic \textbf{E}valuation.