Papers with evaluation of unsupervised cross-lingual models
A Call for More Rigor in Unsupervised Cross-lingual Learning (2020.acl-main)
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| Challenge: | Existing research on unsupervised cross-lingual learning has focused on purely unsupervised learning without any parallel data for most of the world's languages. |
| Approach: | They propose to define "multilingual learning" as learning a common model for two or more languages from raw text, without any downstream task labels. |
| Outcome: | The proposed model is based on a model with no parallel data and abundant monolingual data. |