Low-resource languages, such as Baltic languages, benefit from Large Multilingual Models (LMs) that possess remarkable cross-lingual transfer performance capabilities. This work is an interpretation and analysis study into cross-lingual representations of Multilingual LMs. Previous works hypothesized that these LMs internally project representations of different languages into a shared cross-lingual space. However, the literature produced contradictory results. In this paper, we revisit the prior work claiming that "BERT is not an Interlingua" and show that different languages do converge to a shared space in such language models with another choice of pooling strategy or similarity index. Then, we perform cross-lingual representational analysis for the two most popular multilingual LMs employing 378 pairwise language comparisons. We discover that while most languages share joint cross-lingual space, some do not. However, we observe that Baltic languages do belong to that shared space. The code is available at https://github.com/TartuNLP/xsim.
翻译:波罗的海语言等低资源语言受益于具有卓越的跨语言转让性能的大型多语言模式(LMs),这项工作是对多语言LM的跨语言代表性的口译和分析研究。以前的工作假设,这些LMs内部项目将不同语言纳入一个共同的跨语言空间。然而,文献产生了自相矛盾的结果。在本文中,我们重新审视先前的工作,声称“BERT不是一个Interlingua”,并表明不同语言的确会与这种语言模式中的共享空间相汇合,而采用另一种选择的集合战略或类似指数。然后,我们对两种最受欢迎的多语言LMs进行了跨语言代表性分析,使用378对对口语言比较。我们发现,虽然大多数语言共享共同的跨语言空间,但有些没有。但我们认为,波罗的海语言属于这一共享空间。该代码可在https://github.com/TartuNP/xsim查阅。