All datasets / HPAI-BSC
HPAI-BSC/CareQA
The declared licence (apache-2.0) is classified as permissive.
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- apache-2.0, from the tagEvidence: README.md at 1d976cc
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Citation text from the card
@inproceedings{arias-duart-etal-2025-automatic,
title = "Automatic Evaluation of Healthcare {LLM}s Beyond Question-Answering",
author = "Arias-Duart, Anna and
Martin-Torres, Pablo Agustin and
Hinjos, Daniel and
Bernabeu-Perez, Pablo and
Ganzabal, Lucia Urcelay and
Mallo, Marta Gonzalez and
Gururajan, Ashwin Kumar and
Lopez-Cuena, Enrique and
Alvarez-Napagao, Sergio and
Garcia-Gasulla, Dario",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
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)",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-short.10/",
pages = "108--130",
ISBN = "979-8-89176-190-2",
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
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dataset_licence({ "id": "HPAI-BSC/CareQA" })
signal: "permissive"
stated_licence: "apache-2.0"
sources: 0