What makes multilingual BERT multilingual?
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Abstract (arXiv)
Recently, multilingual BERT works remarkably well on cross-lingual transfer tasks, superior to static non-contextualized word embeddings. In this work, we provide an in-depth experimental study to supplement the existing literature of cross-lingual ability. We compare the cross-lingual ability of non-contextualized and contextualized representation model with the same data. We found that datasize and context window size are crucial factors to the transferability.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 20 Oct 2020.
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1 paper.
- 2022Assessment of Massively Multilingual Sentiment Classifiers11 Apr 2022