Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning

Local Superior Soups improves client training and pre-trained model adaptation in federated learning through regularized model interpolation.

FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation

FedSoup uses selective model interpolation to balance local and global performance, reduce overfitting, and seek flat minima for improved generalization.