GeoSkill lets vision-language models improve geolocation accuracy and reasoning by maintaining an evolving Skill-Graph that grows through autonomous analysis of successful and failed rollouts on web-scale image data.
InInternational conference on ma- chine learning, pages 19730–19742
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IMAGEO-Bench evaluates 10 LLMs on image geolocalization across global street scenes, US POIs, and private images, revealing closed-source model advantages and biases favoring high-resource regions.
EVian decomposes vision-language model responses into three cognitive components and audits them along consistency, coherence, and accuracy axes, showing that a small curated subset outperforms much larger training sets.
citing papers explorer
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Skill-Conditioned Visual Geolocation for Vision-Language Models
GeoSkill lets vision-language models improve geolocation accuracy and reasoning by maintaining an evolving Skill-Graph that grows through autonomous analysis of successful and failed rollouts on web-scale image data.
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From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models
IMAGEO-Bench evaluates 10 LLMs on image geolocalization across global street scenes, US POIs, and private images, revealing closed-source model advantages and biases favoring high-resource regions.
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Evian: Towards Explainable Visual Instruction-tuning Data Auditing
EVian decomposes vision-language model responses into three cognitive components and audits them along consistency, coherence, and accuracy axes, showing that a small curated subset outperforms much larger training sets.