Federated Prompt Learning for Personalized On-Device Weather Forecasting

FedPoD, a communication-efficient framework, addresses the challenges of data heterogeneity among devices and data homogeneity within individual clients during federated learning for on-device weather forecasting. It uses adaptive prompt tuning and dynamic graph modeling to enable highly customized models while maintaining communication efficiency.