A Dataset for Evaluating Large Language Models on Chinese National Medical Licensing Examinations

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Authors: Hui Zong, Bairong Shen
Cited by: 1

Abstract

The dataset integrates question-answer pairs from three sources, including PubMed, GitHub, and MedExamLLM. CNMLEQA comprises two subsets: CNMLEQA-10k (9,890 questions) and CNMLEQA-3k (2,949 questions), each consisting of multiple-choice questions with five options and one correct answer. Questions are annotated with key dimensions including: (1) question type (knowledge-based or case-based), (2) auxiliary metadata such as examination year, 3) clinical scenario information across five dimensions: disease or diagnosis, surgery, medication, laboratory examination, and symptom or sign. Annotation was conducted by clinical experts.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 March 2026
Language
CMN
Document type
Dataset