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Updated: May 11, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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

Published on: December 6, 2024

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RoBIn:基于变压器的模型,用于与机器阅读理解的偏差推断风险

Abel Corrêa Dias1, Viviane Pereira Moreira1, João Luiz Dihl Comba1

  • 1Instituto de Informatica, Av. Bento Goncalves 9500 - Caixa Postal 15064, Porto Alegre, 91501-970, Rio Grande do Sul, Brazil.

Journal of biomedical informatics
|April 18, 2025
PubMed
概括

临床试验中自动化偏差风险 (RoB) 评估现在可以使用RoBIn,这是一种基于变压器的新型模型. RoBIn的性能优于现有的方法,包括大型语言模型 (LLM),用于高效和可扩展的临床研究评估.

关键词:
分类模型的分类模型.深度学习是一种深度学习.基于证据的医学是基于证据的医学.机器阅读理解 机器阅读理解自然语言处理自然语言处理.偏见的风险 偏见的风险系统审查是系统的审查.

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