Papers with ELRL translation

1 papers
SrcMix: Mixing of Related Source Languages Benefits Extremely Low-resource Machine Translation (2026.findings-eacl)

Copied to clipboard

Challenge: Multilingual models are widely used for machine translation, but their effectiveness for extremely low-resource languages (ELRLs) is dependent on how related languages are incorporated during fine-tuning.
Approach: They propose a source-side mixing strategy that combines related ELRLs during fine-tuning while constraining the decoder to a single target language.
Outcome: The proposed approach improves performance in high-resource to ELRL translations and in mid-resourced to MT translations.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations