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pro vyhledávání: '"Piergentili, Andrea"'
Machine translation (MT) models are known to suffer from gender bias, especially when translating into languages with extensive gendered morphology. Accordingly, they still fall short in using gender-inclusive language, also representative of non-bin
Externí odkaz:
http://arxiv.org/abs/2405.08477
Gender-neutral translation (GNT) that avoids biased and undue binary assumptions is a pivotal challenge for the creation of more inclusive translation technologies. Advancements for this task in Machine Translation (MT), however, are hindered by the
Externí odkaz:
http://arxiv.org/abs/2402.06041
Gender inequality is embedded in our communication practices and perpetuated in translation technologies. This becomes particularly apparent when translating into grammatical gender languages, where machine translation (MT) often defaults to masculin
Externí odkaz:
http://arxiv.org/abs/2310.05294
Gender inclusivity in language technologies has become a prominent research topic. In this study, we explore gender-neutral translation (GNT) as a form of gender inclusivity and a goal to be achieved by machine translation (MT) models, which have bee
Externí odkaz:
http://arxiv.org/abs/2301.10075
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