Shanghao Shi, Jian Xiao, Hao Li, Yuanhaur Chang, Yevgeniy Vorobeychik, Nathan Jacobs, Neal Patwari, Ning Zhang · 2026 · arXiv
DOI: 10.48550/arXiv.2610.30439 · open-access PDF
Um den Mechanismus hinter einer solchen feinkörnigen Lokalisierung zu verstehen, entwickeln wir GeoTrace, einen strukturierten Argumentationsschlag, der zeigt, wie Modelle Standortrelevante visuelle Hinweise extrahieren und sie durch grobe bis feine geografische Argumentation zusammensetzen.
Machine translation (Meta M2M100); the English original follows.
Recent large reasoning models can infer where ordinary photos were taken using only visual information, creating a serious location privacy risk even when metadata and obvious geographic identifiers are removed. To understand the mechanism behind such fine-grained localization, we develop GeoTrace, a structured reasoning attack that exposes how models extract location-relevant visual clues and compose them through coarse-to-fine geographic reasoning. We evaluate GeoTrace on a worldwide benchmark of 525 ordinary images spanning natural, urban, residential, and human-centered scenes while exclud
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