Vision-language models display large performance differences and clear limits in zero-shot country-level geolocalization from ground-view photos, with semantic cues helping coarse guesses but failing on fine details.
Geox-bench: Benchmarking cross-view geo-localization and pose estimation capabilities of large multimodal models
2 Pith papers cite this work. Polarity classification is still indexing.
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MapTab is a new multimodal benchmark with 328 images and nearly 200k queries that shows current MLLMs have substantial difficulty with multi-criteria route planning when visual and tabular information must be combined.
citing papers explorer
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Where Do Vision-Language Models Fail? World Scale Analysis for Image Geolocalization
Vision-language models display large performance differences and clear limits in zero-shot country-level geolocalization from ground-view photos, with semantic cues helping coarse guesses but failing on fine details.
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MapTab: Are MLLMs Ready for Multi-Criteria Route Planning in Heterogeneous Graphs?
MapTab is a new multimodal benchmark with 328 images and nearly 200k queries that shows current MLLMs have substantial difficulty with multi-criteria route planning when visual and tabular information must be combined.