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KorMedMCQA: Multi-Choice Question Answering Benchmark for Korean Healthcare Professional Licensing Examinations
March 5, 2024, 2:52 p.m. | Sunjun Kweon, Byungjin Choi, Minkyu Kim, Rae Woong Park, Edward Choi
cs.CL updates on arXiv.org arxiv.org
Abstract: We introduce KorMedMCQA, the first Korean multiple-choice question answering (MCQA) benchmark derived from Korean healthcare professional licensing examinations, covering from the year 2012 to year 2023. This dataset consists of a selection of questions from the license examinations for doctors, nurses, and pharmacists, featuring a diverse array of subjects. We conduct baseline experiments on various large language models, including proprietary/open-source, multilingual/Korean-additional pretrained, and clinical context pretrained models, highlighting the potential for further enhancements. We make …
abstract arxiv benchmark cs.cl dataset doctors healthcare license licensing multiple nurses professional question question answering questions type
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