一个十年的性别偏见在机器翻译
Beatrice Savoldi1, Jasmijn Bastings2, Luisa Bentivogli1
1Fondazione Bruno Kessler, Trento, Italy.
Patterns (New York, N.Y.)
|June 27, 2025
概括
机器翻译 (MT) 中的性别偏见仍然存在,尽管经过了数十年的研究. 审查显示没有简单的技术修复,强调需要以用户为中心的多语言方法来应对复杂的翻译挑战.
科学领域:
- 计算语言学 计算语言学
- 自然语言处理自然语言处理.
- 人工智能的人工智能
背景情况:
- 机器翻译 (MT) 中的性别偏见已经是一个持续的问题超过十年.
- 社会,语言和技术的转变影响了MT研究的格局.
- 早期对快速技术解决方案的乐观态度已经让位于对问题的更复杂的理解.
研究的目的:
- 审查100多项关于MT性别偏见的研究.
- 确定研究中的关键趋势,进展和持续存在的差距.
- 检查大型语言模型 (LLM) 在解决翻译中的性别偏见方面的作用.
主要方法:
- 对100多项关于MT性别偏见的研究进行了全面的文献综述.
- 分析现有研究的趋势,进展和局限性.
- 探索大型语言模型对翻译中的性别偏见的影响.
主要成果:
- 尽管进行了广泛的研究,但MT中的性别偏见仍然是一个复杂的问题,没有简单的技术解决方案.
- 确定了关键趋势和进展,但仍然存在重大差距.
- 大型语言模型为减轻翻译中的性别偏见带来了挑战和机会.
结论:
- 简单的技术修复不足以解决MT中的性别偏见.
- 未来的研究应该优先考虑以用户为中心,多语言和多文化方法.
- 工作应该更好地根据现实世界的需求进行,并超越纯粹的技术重点.
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