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Disaster social sensing converts public social-media posts into evidence for situational awareness and humanitarian needs, but generative artificial intelligence (AI) can produce plausible messages that resemble eyewitness reports. This study investigates whether text-based AI detectors can reliably distinguish human-a...
CHESTPHENOT is a compact 0.5-3B language model that jointly extracts finding labels, three-class status (present/absent/uncertain), and verbatim supporting evidence spans and demonstrates that locally deployable models can provide competitive and directly auditable radiology-report extraction without relying on externa...
Salient-Q, a saliency-guided vision-language framework that addresses challenges of PHI identification and localization through three architectural innovations, outperforms other baseline models in terms of PHI identification and localization.
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