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Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
Federated learning (FL) is a learning paradigm that enables collaborative training of models using decentralized data. Recently, the utilization of pre-trained weight initialization in FL has been demonstrated to effectively improve model performance. However, the evolving complexity of current pre-
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