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​​Cross-Lingual Ability of Multilingual BERT: An Empirical Study to #ICLR2020

In this work, the authors provide a comprehensive study of the contribution of different components in multilingual #BERT (M-BERT) to its cross-lingual ability.
They study the impact of linguistic properties of the languages, the architecture of the model, and the learning objectives. The experimental study is done in the context of three typologically different languages – #Spanish, #Hindi, & #Russian – & using two conceptually different #NLP tasks, textual entailment & #NER.

Also, they construct a new corpus – Fake-English (#enfake), by shifting the Unicode of each character in English Wikipedia text by a large constant so that there is strictly no character overlap with any other Wikipedia text.
And, in this work, they consider Fake-English as a different language.

Among their key conclusions are the fact that the lexical overlap between languages plays a negligible role in the cross-lingual success, while the depth of the network is an integral part of it.

paper: https://arxiv.org/abs/1912.07840