Title: NileChat: Towards Linguistically Diverse and Culturally Aware LLMs for Local Communities
Abstract: https://arxiv.org/abs/2505.18383
EgyMMLU is a benchmark designed to evaluate the performance of large language models in Egyptian Arabic. It contains 22,027 multiple-choice questions covering 44 subjects, translated from parts of the Massive Multitask Language Understanding (MMLU) and ArabicMMLU benchmarks. The dataset was translated using google/gemma-3-27b-it.
Homepage: https://huggingface.co/datasets/UBC-NLP/EgyMMLU
@article{mekki2025nilechatlinguisticallydiverseculturally,
title={NileChat: Towards Linguistically Diverse and Culturally Aware LLMs for Local Communities},
author={Abdellah El Mekki and Houdaifa Atou and Omer Nacar and Shady Shehata and Muhammad Abdul-Mageed},
year={2025},
eprint={2505.18383},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2505.18383},
}
egymmlu: evaluates all EgyMMLU tasks.
Source-based tags:
egymmlu_mmlu: evaluates EgyMMLU tasks that were translated from MMLU.egymmlu_ar_mmlu: evaluates EgyMMLU tasks that were translated from ArabicMMLU.
Category-based tags:
egymmlu_stem: evaluates EgyMMLU STEM tasks.egymmlu_social_sciences: evaluates EgyMMLU social sciences tasks.egymmlu_humanities: evaluates EgyMMLU humanities tasks.egymmlu_language: evaluates EgyMMLU language tasks.egymmlu_other: evaluates other EgyMMLU tasks.
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