Papers with PARC

1 papers
Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages (2023.findings-acl)

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Challenge: Multilingual pretrained language models (MPLMs) perform strongly in cross-lingual transfer.
Approach: They propose to augment context with similar sentences retrieved from a high-resource language (HRL) they find a significant correlation between cross-lingual transfer performance and similarity between high- and low-resourced languages .
Outcome: The proposed model outperforms finetuning by 3.7% on three downstream tasks with multilingual parallel test sets across 10 LRLs covering 6 language families in unlabeled and labeled settings.

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