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Author

Maite Melero

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Open access 2026

Linguistic Knowledge-Infused Fine-Tuning for Mitigating Gender Bias in Machine Translation

Large Language Models (LLMs) achieve strong performance in machine translation (MT) but often encode gender bias, particularly when translating from non-gendered into gendered languages. This paper introduces a fine-tuning strategy to mitigate such bias in English → Spanish and English → Catalan translation. Using para...

Luis Ernesto Garcia-Estrada, Audrey Mash, C. Escolano et al. · 0 citations
#natural language process... Preprint Sep 2026

SalamandraTA at WMT 2026 Terminology Shared Task: Hard Examples Are Better Teachers

Terminology-aware translation asks for more than a correct translation: the output must use the exact terms a glossary prescribes. The standard recipe, fine-tuning on glossary-annotated translation pairs, hides an inefficiency: for most examples the glossary prescribes exactly what the model would have produced anyway,...

Xi-Xian Liao, Maite Melero · 0 citations

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