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Myanmar XNLI: building a dataset and exploring low-resource approaches to natural language inference with Myanmar.

Despite dramatic recent progress in NLP, it is still a major challenge to apply Large Language Models (LLM) to low-resource languages. This is made visible in benchmarks such as Cross-Lingual Natural Language Inference (XNLI), a key task that demonstrates cross-lingual capabilities of NLP systems ac...

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Publicado en:Language Resources & Evaluation Vol. 59; no. 3; pp. 3267 - 3311
Autores principales: Htet, Aung Kyaw, Dras, Mark
Formato: Artículo
Publicado: Springer Nature Sep2025
Materias:
Low-resource languages
Data augmentation
Acquisition of data
Citizen science
Natural languages
Natural language processing
Language models
Myanmar
Acceso en línea:Ver este registro en EBSCOhost