Papers with large-scale multilingual evaluations

1 papers
Quantifying Language Disparities in Multilingual Large Language Models (2025.emnlp-main)

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Challenge: Contemporary NLP development relies on digital language datasets to build large language models.
Approach: They propose a framework that disentangles confounding variables and introduces interpretable metrics to quantify model performance and language disparities.
Outcome: The proposed framework provides a more reliable measurement of model performance and language disparities for low-resource languages.

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