ALIGN-FL: Advancing Federated Learning with Architecture-Agnostic Generative Components

This research explores a novel approach to federated learning, focusing on architecture independence and generative component sharing. The key strength lies in its potential to improve the efficiency and robustness of federated learning across diverse client architectures.