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20242026
most citedDualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations

7 citations · 7 across the 3 of their papers we have counts for

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cs.AI2026

From Coordinate Matching to Structural Alignment: Rethinking Prototype Alignment in Heterogeneous Federated Learning

Xinghao Wu, Jianwei Niu, Guogang Zhu +3

Heterogeneous federated learning (HtFL) aims to enable collaboration among clients that differ in both data distributions and model architectures. Prototype-based methods, which co…