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Updated: Sep 10, 2025

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用于生物医学命名实体识别的大型语言模型的资源效率指令调整

Hui Liu1, Ziyi Chen2, Peilin Li3

  • 1School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, No. 96, JinZhai Road Baohe District, Hefei, 230026, Anhui, China; Suzhou Institute for Advanced Research, University of Science and Technology of China, No. 166, Renai Road, Suzhou, 215123, Jiangsu, China; Department of Precision Machinery and Precision Instruments, University of Science and Technology of China, No. 96, JinZhai Road Baohe District, Hefei, 230026, Anhui, China.

Journal of biomedical informatics
|August 23, 2025
PubMed
概括

参数有效微调 (PEFT) 优化了大型语言模型 (LLM) 用于更少的资源进行生物医学命名实体识别 (BioNER). 由此产生的NERLlama3.1模型实现了高性能和强大的通用化,性能优于完全微调的模型.

关键词:
生物NER一个LLM多任务生物NER一个PEFT没有.自我一致性的NER提示

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