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MarIA and BETO are sexist: evaluating gender bias in large language models for Spanish.

The study of bias in language models is a growing area of work, however, both research and resources are focused on English. In this paper, we make a first approach focusing on gender bias in some freely available Spanish language models trained using popular deep neural networks, like BERT or RoBER...

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Published in:Language Resources & Evaluation Vol. 58; no. 4; pp. 1387 - 1418
Main Authors: Garrido-Muñoz, Ismael, Martínez-Santiago, Fernando, Montejo-Ráez, Arturo
Format: Article
Published: Springer Nature Dec2024
Subjects:
Artificial neural networks
Language models
Spanish language
Deep learning
Sexism
Algorithmic bias
Online Access:View this record in EBSCOhost