实例特定模型扰动改善了通用化的零射击学习

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Updated: Jul 1, 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

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Guanyu Yang1, Kaizhu Huang2, Rui Zhang3

  • 1Data Science Research Center, Duke Kunshan University, Kunshan, 215316, China guanyu.yang@dukekunshan.edu.cn.

Neural computation
|March 8, 2024
PubMed
概括

这项研究引入了一种新的对抗性训练方法,以改善通用零射击学习 (GZSL). 该方法通过使预测对未见类更敏感,同时保持可见类的稳定性来提高模型准确性.

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