Papers with language knowledge transfer

2 papers
Pretrained Bidirectional Distillation for Machine Translation (2023.acl-long)

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Challenge: Existing studies have focused on language knowledge transfer from pretrained models to neural machine translation models.
Approach: They propose to use masked language pretraining to efficiently transfer bidirectional language knowledge to NMT models.
Outcome: The proposed method can significantly improve machine translation performance and achieve competitive or even better results than previous methods.
CL-ReLKT: Cross-lingual Language Knowledge Transfer for Multilingual Retrieval Question Answering (2022.findings-naacl)

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Challenge: Existing approaches to cross-lingual question answering use sentence embedding to map documents and questions in multiple languages . a novel cross-linguistic approach to cross language-retrieval question answering is proposed . our method outperforms competitors in 19 out of 21 settings of CL-ReQA .
Approach: They propose a cross-lingual language knowledge transfer framework for cross-linguistic question answering . they use a multilingual sentence embedding technique to create a linguistic embeddable space .
Outcome: The proposed method outperforms current state-of-the-art methods in 19 out of 21 settings of CL-ReQA.

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