Cross-Linguistic Syntactic Difference in Multilingual BERT: How Good is It and How Does It Affect Transfer?

Ningyu Xu, Tao Gui, Ruotian Ma, Qi Zhang, Jingting Ye, Menghan Zhang, Xuanjing Huang
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引用次数: 3

Abstract

Multilingual BERT (mBERT) has demonstrated considerable cross-lingual syntactic ability, whereby it enables effective zero-shot cross-lingual transfer of syntactic knowledge. The transfer is more successful between some languages, but it is not well understood what leads to this variation and whether it fairly reflects difference between languages. In this work, we investigate the distributions of grammatical relations induced from mBERT in the context of 24 typologically different languages. We demonstrate that the distance between the distributions of different languages is highly consistent with the syntactic difference in terms of linguistic formalisms. Such difference learnt via self-supervision plays a crucial role in the zero-shot transfer performance and can be predicted by variation in morphosyntactic properties between languages. These results suggest that mBERT properly encodes languages in a way consistent with linguistic diversity and provide insights into the mechanism of cross-lingual transfer.
多语言BERT的跨语言句法差异:它有多好?它如何影响迁移?
多语言BERT (mBERT)已经证明了相当大的跨语言句法能力,从而实现了句法知识的有效零概率跨语言迁移。一些语言之间的迁移更为成功,但人们并不清楚是什么导致了这种差异,以及它是否公平地反映了语言之间的差异。在这项工作中,我们研究了在24种不同类型的语言背景下由mBERT诱导的语法关系的分布。我们证明了不同语言分布之间的距离与语言形式的句法差异高度一致。这种通过自我监督习得的差异在零迁移表现中起着至关重要的作用,并且可以通过语言间形态句法特性的差异来预测。这些结果表明,mBERT以一种符合语言多样性的方式对语言进行了适当的编码,并为跨语言迁移的机制提供了新的见解。
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