Dual prompt personalized federated learning in foundation models

Dual prompt personalized federated learning in foundation models

Abstract Personalized federated learning (PFL) has garnered significant attention for its ability to address heterogeneous client data distributions while preserving data privacy. However, when local client data is limited, deep learning models often suffer from insufficient training, leading to sub...

Full description

Saved in:
Bibliographic Details
Main Authors: Ying Chang, Xiaohu Shi, Xiaohui Zhao, Zhaohuang Chen, Deyin Ma
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Personalized federated learning
Foundation models
Client heterogeneity
Adaptive aggregation strategy
Online Access:https://doi.org/10.1038/s41598-025-11864-4
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-11864-4

Similar Items