AI RESEARCH
Is She Even Relevant? When BERT Ignores Explicit Gender Cues
arXiv CS.CL
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ArXi:2605.07622v1 Announce Type: new Gender bias in large language models has primarily been investigated for English, while languages with grammatical or morphological gender remain comparatively understudied. This paper investigates how and when gender information emerges in a Dutch BERT model trained from scratch, offering one of the first checkpoint-level analyses of bias formation in a Transformer architecture for a language combining overt morphological gender marking and generic forms. By extracting contextual embeddings throughout.