Current State-of-the-Art of Bias Detection and Mitigation in Machine Translation for African and European Languages: a Review
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Abstract (arXiv)
Studying bias detection and mitigation methods in natural language processing and the particular case of machine translation is highly relevant, as societal stereotypes might be reflected or reinforced by these systems. In this paper, we analyze the state-of-the-art with a particular focus on European and African languages. We show how the majority of the work in this field concentrates on few languages, and that there is potential for future research to cover also the less investigated languages to contribute to more diversity in the research field.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 23 of its 39 references that are in the map. First posted on arXiv 28 Oct 2024.
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23 of 39 references.
References · 23
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