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Updated: Jul 25, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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使用深度LSD在GAN潜伏空间中构建运算符,在现实空间中具有意义

J Quetzalcóatl Toledo-Marín1,2, James A Glazier1

  • 1Luddy School of Informatics, Computing and Engineering, Biocomplexity Institute, Indiana University, Bloomington, IN, United States of America.

PloS one
|June 29, 2023
PubMed
概括

研究人员开发了准自身载体来分析生成对抗网络 (GAN). 这些向量简化了隐藏空间,使得标记特征的一对一映射成为可能,并改善了像图像消噪等任务的数据处理.

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