T. Paunesku

XRF-to-Optical Field-of-View Localization with Vision Language Models

This paper evaluates training-free vision language model (VLM) localization on two datasets representing same-section high-correspondence and adjacent-section low-correspondence imaging and tests unconstrained and metadata-constrained search and VLMs with geometric controls, classical template matching, and two alternative training-free approaches.