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Updated: Jun 6, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

504

通过最佳运输和对抗性学习增强开放式域名适应性

Qing Tian1, Yi Zhao2, Keyang Cheng3

  • 1School of Software, Nanjing University of Information Science and Technology, Nanjing China; Wuxi Institute of Technology, Nanjing University of Information Science and Technology, Wuxi China; MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing China.

Neural networks : the official journal of the International Neural Network Society
|November 24, 2024
PubMed
概括

开放式域调整 (OSDA) 方法与目标域数据发生冲突. 我们的最佳传输和对抗性学习 (OTAL) 框架通过更好地区分已知的和未知的类来改善知识传输.

关键词:
反对性的学习学习.开放式设置域名适应最佳的运输方式是最佳运输方式.

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