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Federated learning can overcome data silos, but struggles when clients have different label relationships; FedHarmony shows how to harmonize these differences, leading to better performance.
Laplacian kernels offer a theoretically sound and empirically superior alternative to Gaussian kernels for linear attention, finally bridging the gap between efficient computation and expressive power in Transformers.
Forget generic robot demos – this work introduces a complete pipeline and dataset for AI-powered massage robots that can understand language and identify acupoints.
