面向非洲与欧洲语言的机器翻译中偏见检测与缓解的当前研究前沿：综述
Current State-of-the-Art of Bias Detection and Mitigation in Machine Translation for African and European Languages: a Review
AI总结：
本综述聚焦非洲与欧洲语言的机器翻译偏见检测与缓解研究，分析前沿进展后发现现有研究多集中于少数语言，提出拓展低研究度语言可提升领域多样性。
摘要：
研究自然语言处理中的偏见检测与缓解方法，以及机器翻译这一特定场景，具有高度现实意义，因为社会刻板印象可能会被这类系统反映甚至强化。本文聚焦欧洲与非洲语言，分析了该领域的前沿研究进展。我们发现，该领域的大多数研究仅集中在少数几种语言上，未来研究有潜力覆盖更多研究较少的语言，从而为提升该研究领域的多样性做出贡献。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
