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Feda Negesse

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Review Open access Oct 2026

A scoping review of transformer and large language model approaches for word sense disambiguation in multilingual and low resource settings from 2019 to 2026

In natural language processing, word sense disambiguation (WSD) is still a significant difficulty, especially in low-resource, multilingual environments with few annotated resources. Contextual semantic representation and WSD performance have been enhanced by recent developments in transformer architectures and l...

Liyachew Edeti, M. Meshesha, Feda Negesse · 0 citations
Open access Jul 2026

Low resource word sense disambiguation in Oromo with fine tuned small transformers.

Results show that contextual transformer representations are quite successful for low-resource WSD, although there is still a significant class imbalance that limits performance.

Liyachew Edeti, Million Meshesha, Feda Negesse · 0 citations

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