Papers with selective knowledge distillation mechanism
Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help? (2021.findings-emnlp)
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| Challenge: | Multilingual Neural Machine Translation (MNMT) trains a single model that supports translation between multiple languages . transferring knowledge from a diverse set of languages degrades the translation performance due to negative transfer. |
| Approach: | They propose a hierarchical knowledge distillation approach to train multilingual models . they use typological features and phylogeny to overcome negative transfer issue . |
| Outcome: | The proposed approach avoids negative transfer effect by capitalising on language groups generated according to typological features and phylogeny of languages. |