相关实验视频

Updated: Jul 30, 2026

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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一个保护隐私的联合元学习框架,用于跨项目在软件系统中的缺陷预测

Jhansi Lakshmi Potharlanka1, Kareena Yashmin Shaik2, Bharath Kumar N3

  • 1Department of Computer Science and Engineering, Vignan's Foundation for Science Technology and Research, Guntur, 522213, India. laxmi.jhansi@gmail.com.

Scientific reports
|November 18, 2025
PubMed
概括

高效通信联合元学习 (ECFML) 框架通过使用紧,高效的模型来改进软件缺陷预测. 它在保持隐私和减少联合学习环境中的通信开销的同时,实现了竞争力的结果.

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