Contrastive Learning for Morphological Disambiguation Using Large Language Models in Low-Resource Settings
In this paper, a contrastive learning approach for morphological disambiguation (MD) using large language models (LLMs) is presented. A contrastive loss function is introduced for training the approach, which reduces the distance between the correct analysis and contextual embeddings while maintaini...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2024-11-01
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| Colecção: | Applied Sciences |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/2076-3417/14/21/9992 |
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