维西纳尔高斯转换:通过源信息标签一致性重新思考源无源域调整

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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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Jing Wang, Yongchao Xu, Jing Tang

    IEEE transactions on pattern analysis and machine intelligence
    |October 15, 2025
    PubMed
    概括

    这项研究介绍了用于无源域适应 (SFDA) 的Vicinal Gaussian Transform (VGT). 基于能源的VGT (EBVGT) 方法通过缩小协差来提高适应性,提高标签一致性,而无需源数据.

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