Preprint Open access
USAI-Quant: A Quantitative Reasoning Benchmark for Vision-Language Models in Built Environments
Large vision-language models (VLMs) have emerged as a powerful paradigm for urban and spatial AI. However, current state-of-the-art large VLMs still struggle with quantitative reasoning on remote sensing imagery. Existing benchmarks and algorithms are predominantly based on qualitative Visual Question Answering (VQA), …