Tabla de Contenidos: :: Library Catalog

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Ao, Yan, Bin, Cai, Bingfeng, Li, Chenxi, Zhao, Cunzhong, Yao, Fugen, Liu, Gaoqiang, Jiang, Guanjun, Xu, Jian, Dong, Liang, Sun, Liansheng, Zhang, Rongshen, Gui, Xiaolei, Liu, Xin, Shang, Xin, Wu, Yao, Cao, Yu, Ma, Zhenxin, Jia, Zhuang
Formato:	Preprint
Publicado:	2025
Materias:	Artificial Intelligence
Acceso en línea:	https://arxiv.org/abs/2508.11894
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Tabla de Contenidos:

Recent advancements in large language models have significantly accelerated their adoption in healthcare applications, including AI-powered medical consultations, diagnostic report assistance, and medical search tools. However, medical tasks often demand highly specialized knowledge, professional accuracy, and customization capabilities, necessitating a robust and reliable foundation model. QuarkMed addresses these needs by leveraging curated medical data processing, medical-content Retrieval-Augmented Generation (RAG), and a large-scale, verifiable reinforcement learning pipeline to develop a high-performance medical foundation model. The model achieved 70% accuracy on the Chinese Medical Licensing Examination, demonstrating strong generalization across diverse medical benchmarks. QuarkMed offers a powerful yet versatile personal medical AI solution, already serving over millions of users at ai.quark.cn.

Ejemplares similares