AI's Blind Spots: Geographic Knowledge and Diversity Deficit in Generated Urban Scenario

Understand

Diffusion-based text-to-image models are increasingly used for urban analysis and scenario generation, but their geographic knowledge and representational biases remain poorly understood.

• We evaluate FLUX 1-schnell and Stable Diffusion 3.5-Large in the United States by generating 150 street-view images for each state, each state capital, and a generic "USA" prompt.
• Images are embedded with DINO-v2 ViT-S/14 and compared with Fr\'echet Inception Distance (FID).
• Pairwise FID clustering shows that geographically proximate states and capitals often group together, indicating implicit geographic structure.