Papers with cross-lingual transfer abilities

1 papers
Soft Language Clustering for Multilingual Model Pre-training (2023.acl-long)

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Challenge: Multilingual pre-trained language models have demonstrated impressive (zero-shot) cross-lingual transfer abilities, however, their performance is hindered when the target language has distant typology from the source language or when pre-training data is limited in size.
Approach: They propose a method that contextually retrieves prompts as flexible guidance for encoding instances conditionally.
Outcome: The proposed method improves on the XTREME task and also for low-resource languages in unsupervised sentence retrieval.

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