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Updated: Jun 11, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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通过通用域资源增强生物医学命名实体识别

Yu Yin1, Hyunjae Kim2, Xiao Xiao1

  • 1Department of Computer Science, University of Liverpool, Liverpool L69 3DR, United Kingdom.

Journal of biomedical informatics
|October 5, 2024
PubMed
概括

通过使用通用域数据集,GERBERA增强了生物医学命名实体识别 (BioNER) 模型. 这种具有成本效益的转移学习方法提高了BioNER的性能,尤其是在有限的生物医学数据的情况下.

关键词:
生物医学命名实体识别技术自然语言处理自然语言处理.转移学习学习 转移学习

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