AI RESEARCH
GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction
arXiv CS.AI
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ArXi:2605.09973v1 Announce Type: cross Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains difficult: PII spans are heterogeneous, locale-dependent, context-sensitive, and often embedded in noisy or semi-structured documents. We present GLiNER2-PII, a small 0.3B-parameter model adapted from GLiNER2 and designed to recognize a broad taxonomy of 42 PII entity types at character-span resolution