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Updated: Jul 9, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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基于图形嵌入的异质域适应与域不变特征学习和维护分布顺序的分布顺序

Wenxu Wang1, Zhenbo Li2, Weiran Li1

  • 1College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China; National Innovation Center for Digital Fishery, China Agricultural University, Beijing, 100083, China.

Neural networks : the official journal of the International Neural Network Society
|November 30, 2023
PubMed
概括

这项研究引入了一个新的框架 (GHID) 异质域适应 (HDA),以提高模型的准确性和稳定性. GHID有效地对齐域,并保持数据分布,克服了先前HDA方法的局限性.

关键词:
双向强大的跨域对齐.保持分配顺序的分配顺序.图形嵌入式嵌入式不同质的领域适应适应.

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