Datasets:
Tasks:
Visual Question Answering
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
remote-sensing
satellite-imagery
geospatial
earth-observation
spatial-reasoning
quantitative-reasoning
DOI:
License:
Link the SQuID GitHub repository
Browse files
README.md
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<p align="center">
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<a href="https://arxiv.org/abs/2601.13401"><img src="https://img.shields.io/badge/arXiv-2601.13401-b31b1b.svg"></a>
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<a href="https://github.com/PeterAMassih/
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</p>
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SQuID asks vision-language models to measure satellite images: count objects, compute areas and reason about distances. Every answer is computed from pixel-level masks.
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<p align="center">
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<a href="https://arxiv.org/abs/2601.13401"><img src="https://img.shields.io/badge/arXiv-2601.13401-b31b1b.svg"></a>
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<a href="https://github.com/PeterAMassih/SQuID"><img src="https://img.shields.io/badge/GitHub-code-181717.svg?logo=github"></a>
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</p>
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SQuID asks vision-language models to measure satellite images: count objects, compute areas and reason about distances. Every answer is computed from pixel-level masks.
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