{
 "id": "HPAI-BSC/CareQA",
 "owner": "HPAI-BSC",
 "name": "CareQA",
 "downloads": 3256,
 "likes": 18,
 "last_modified": "2025-05-21T08:01:06.000Z",
 "stated_licence": "apache-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "question-answering"
 ],
 "citation": "@inproceedings{arias-duart-etal-2025-automatic,\n    title = \"Automatic Evaluation of Healthcare {LLM}s Beyond Question-Answering\",\n    author = \"Arias-Duart, Anna  and\n      Martin-Torres, Pablo Agustin  and\n      Hinjos, Daniel  and\n      Bernabeu-Perez, Pablo  and\n      Ganzabal, Lucia Urcelay  and\n      Mallo, Marta Gonzalez  and\n      Gururajan, Ashwin Kumar  and\n      Lopez-Cuena, Enrique  and\n      Alvarez-Napagao, Sergio  and\n      Garcia-Gasulla, Dario\",\n    editor = \"Chiruzzo, Luis  and\n      Ritter, Alan  and\n      Wang, Lu\",\n    booktitle = \"Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)\",\n    month = apr,\n    year = \"2025\",\n    address = \"Albuquerque, New Mexico\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2025.naacl-short.10/\",\n    pages = \"108--130\",\n    ISBN = \"979-8-89176-190-2\",\n    abstract = \"Current Large Language Models (LLMs) benchmarks are often based on open-ended or close-ended QA evaluations, avoiding the requirement of human labor. Close-ended measurements evaluate the factuality of responses but lack expressiveness. Open-ended capture the model`s capacity to produce discourse responses but are harder to assess for correctness. These two approaches are commonly used, either independently or together, though their relationship remains poorly understood. This work is foc",
 "signal": "permissive",
 "reason": "The declared licence (apache-2.0) is classified as permissive.",
 "revision": "1d976cc544ccb9dfc96e14439e6840e8a810cec5",
 "stated_evidence": "https://huggingface.co/datasets/HPAI-BSC/CareQA/blob/1d976cc544ccb9dfc96e14439e6840e8a810cec5/README.md",
 "file_evidence": "https://huggingface.co/datasets/HPAI-BSC/CareQA/tree/1d976cc544ccb9dfc96e14439e6840e8a810cec5",
 "card_nc": false
}