以语言为灵感的关系转移为短暂的课堂增量学习

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Updated: Jun 8, 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

505

Yifan Zhao, Jia Li, Zeyin Song

    IEEE transactions on pattern analysis and machine intelligence
    |November 6, 2024
    PubMed
    概括

    这项研究引入了一种新的语言灵感关系转移 (LRT) 方法,用于少量射击类增量学习 (FSCIL). 通过结合视觉和文本数据,LRT增强了对象识别,优于现有的模型.

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