# EgyMMLU ### Paper Title: NileChat: Towards Linguistically Diverse and Culturally Aware LLMs for Local Communities Abstract: [https://arxiv.org/abs/2505.18383](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](https://huggingface.co/datasets/UBC-NLP/EgyMMLU) ### Citation ``` @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}, } ``` ### Groups and Tasks #### Groups * `egymmlu`: evaluates all EgyMMLU tasks. #### Tags 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. ### Checklist For adding novel benchmarks/datasets to the library: * [x] Is the task an existing benchmark in the literature? * [x] Have you referenced the original paper that introduced the task? * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? If other tasks on this dataset are already supported: * [ ] Is the "Main" variant of this task clearly denoted? * [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? * [ ] Have you noted which, if any, published evaluation setups are matched by this variant?