Papers with multilingual pretraining setup

2 papers
The RELX Dataset and Matching the Multilingual Blanks for Cross-Lingual Relation Classification (2020.findings-emnlp)

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Challenge: Current approaches for relation classification are focused on the English language and require lots of training data with human annotations.
Approach: They propose a baseline model based on Multilingual BERT and a new multilingual pretraining setup . they propose 'relationship classification' models that use distant supervision .
Outcome: The proposed model significantly improves the baseline model with distant supervision.
Identifying Elements Essential for BERT’s Multilinguality (2020.emnlp-main)

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Challenge: Multilingual BERT (mBERT) does not use any crosslingual signal during training.
Approach: They propose a multilingual pretraining setup that modifies the masking strategy using VecMap to allow for fast experimentation.
Outcome: The proposed setup with pretrained models with three languages shows that it works well.

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