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...

Full description

Bibliographic Details

Published in:	Language Resources & Evaluation Vol. 59; no. 3; pp. 3267 - 3311
Main Authors:	Htet, Aung Kyaw, Dras, Mark
Format:	Article
Published:	Springer Nature Sep2025
Subjects:	Low-resource languages Data augmentation Acquisition of data Citizen science Natural languages Natural language processing Language models Myanmar
Online Access:	View this record in EBSCOhost