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Updated: Sep 11, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

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GLC++:通过全球-本地聚类和对比的亲和学习来实现源代码免费的通用域调整

Sanqing Qu, Tianpei Zou, Florian Rohrbein

    IEEE transactions on pattern analysis and machine intelligence
    |August 12, 2025
    PubMed
    概括

    本研究介绍了源代码免费通用域调整 (SF-UniDA),以改进面临数据转移的深度学习模型. 新的方法,全球和本地聚类 (GLC) 和GLC++,提高了已知和未知数据类别的分类.

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