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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