Feb. 12, 2024, 5:46 a.m. | Beatrice Savoldi Andrea Piergentili Dennis Fucci Matteo Negri Luisa Bentivogli

cs.CL updates on arXiv.org arxiv.org

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 lack of dedicated parallel data, which are necessary to adapt MT systems to satisfy neutral constraints. For such a scenario, large language models offer hitherto unforeseen possibilities, as they come with the distinct advantage of being versatile in various (sub)tasks when provided with explicit instructions. …

adapt assumptions binary challenge cs.cl data demand gender machine machine translation pivotal prompt systems technologies translation

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