May, 2023
目标无关的性别感知对比学习在多语言机器翻译中缓解偏见
Target-Agnostic Gender-Aware Contrastive Learning for Mitigating Bias in Multilingual Machine Translation
Minwoo Lee, Hyukhun Koh, Kang-il Lee, Dongdong Zhang, Minsung Kim...
TL;DR针对多语言机器翻译模型中明显的性别偏见问题,提出了一种新的缓解方法,Gender-Aware Contrastive Learning,通过伪标签在编码器嵌入中编码性别信息来提高性别准确度并改善其他目标语言的性别准确度。