Papers with Cross-Lingual Transfer Learning

2 papers
UniBridge: A Unified Approach to Cross-Lingual Transfer Learning for Low-Resource Languages (2024.acl-long)

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Challenge: Existing pre-trained language models are weak in addressing cross-lingual transfer tasks.
Approach: They propose a method for initializing embeddings and choosing the right vocabulary size for cross-lingual systems.
Outcome: The proposed method improves the F1-Score in several languages .
Exploring Cross-Lingual Transfer Learning with Unsupervised Machine Translation (2021.findings-acl)

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Challenge: a new CLTL model is proposed to facilitate cross-linguistic transfer learning between distant languages . a key to CLTL is to learn a shared representation space for the given source-target language pair.
Approach: They propose a new CLTL model that integrates machine translation with MT . they use an unannotated data technique to make use of the model's pre-training and fine-tuning .
Outcome: The proposed model achieves better CLTL performance than the baseline model without more annotated data.

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