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News/Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution
arxiv
PublishedJuly 28, 2026 at 4:00 AM

Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution

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arXiv:2607.22546v1 Announce Type: new Abstract: Machine translation (MT) systems continue to produce gender-biased translations. In a time where self-expression is paramount, mistranslations based on default behaviour and stereotyping can lead to harm for users of these systems. To better understand

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