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),...
Dong-Dong Wang, Q. Song, Yu-Zhou Chen et al.
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