DREAM:用于无监督图域适应的双变量框架

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Updated: Sep 12, 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

682

Nan Yin, Li Shen, Mengzhu Wang

    IEEE transactions on pattern analysis and machine intelligence
    |August 5, 2025
    PubMed
    概括

    双变义语义图表挖掘 (DREAM) 通过整合隐式和显式结构语义来解决无监督图域的适应. 这种方法提高了图形分类的准确性,克服了传统消息传递神经网络 (MPNNs) 的局限性.

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