{
 "id": "EC-DGT-AI/EU-MMLU",
 "owner": "EC-DGT-AI",
 "name": "EU-MMLU",
 "downloads": 863,
 "likes": 12,
 "last_modified": "2026-09-29T07:56:13.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "question-answering"
 ],
 "citation": "@article{Gijon2026,\r\n      title={Building a European Multilingual Evaluation Dataset: The MMLU Localisation Project within the EMT Network},\r\n      author={Sánchez-Gijón, P., Valdez, S., Kokkinidou, A., Bellemont, F., Calvo Del Barrio, S., Brasoveanu, M. C.},\r\n      journal={Proceedings of the International Conference on New Trends in Translation and Interpreting Technology},\r\n      year={2026}\r\n    }\r\n\r\n    @article{hendryckstest2021,\r\n      title={Measuring Massive Multitask Language Understanding},\r\n      author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt},\r\n      journal={Proceedings of the International Conference on Learning Representations (ICLR)},\r\n      year={2021}\r\n    }\r\n\r\n    @article{hendrycks2021ethics,\r\n      title={Aligning AI With Shared Human Values},\r\n      author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt},\r\n      journal={Proceedings of the International Conference on Learning Representations (ICLR)},\r\n      year={2021}\r\n    }\r\n    @software{palace2025,\r\n      title = {PALACE: An Open Benchmark Format for LLM Evaluation},\r\n      author = {Altieri, Massimiliano},\r\n      year = {2025},\r\n      institution = {European Commission Joint Research Centre},\r\n      url = {https://code.europa.eu/palace/palace-eval},\r\n      license = {EUPL-1.2}\r\n    }",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "6bf04b0030783b3c9074c8d59416ff761962568a",
 "stated_evidence": "https://huggingface.co/datasets/EC-DGT-AI/EU-MMLU/blob/6bf04b0030783b3c9074c8d59416ff761962568a/README.md",
 "file_evidence": "https://huggingface.co/datasets/EC-DGT-AI/EU-MMLU/tree/6bf04b0030783b3c9074c8d59416ff761962568a",
 "card_nc": false
}