Papers with Multilingual contextual embeddings
Don’t Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings (2020.emnlp-main)
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| Challenge: | Multilingual contextual embeddings have demonstrated state-of-the-art performance in zero-shot cross-lingual transfer learning. |
| Approach: | They show that English dev accuracy makes it difficult to obtain reproducible results . they recommend providing oracle scores alongside zero-shot results if possible . |
| Outcome: | mBERT and XLM have shown strong performance on cross-lingual recognition, text classification, dependency parsing, and other tasks. |
On the Language Neutrality of Pre-trained Multilingual Representations (2020.findings-emnlp)
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| Challenge: | Existing studies have focused on cross-linguality of contextual embeddings . however, they are only moderately language-neutral by default . |
| Approach: | They propose to use unsupervised centering and fitting an explicit projection on parallel data to achieve stronger language neutrality. |
| Outcome: | The proposed model outperforms existing models on XNLI and NER tasks. |