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Updated: Jul 2, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

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在系统性审查中整合大型语言模型:使用ROBINS-I进行偏差评估风险的框架和案例研究

Bashar Hasan1,2, Samer Saadi3,2, Noora S Rajjoub3

  • 1Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, Minnesota, USA Hasan.Bashar@mayo.edu.

BMJ evidence-based medicine
|February 21, 2024
PubMed
概括

大型语言模型 (LLM) 显示,在系统性审查中对偏见风险评估方面,与人类审稿人之间存在温和的共识. 拟议的框架指导了LLM的整合,但人类监督仍然是必不可少的.

关键词:
基于证据的实践.方法 方法 方法作为主题的系统审查.

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