FedSAF shifts prototype alignment in heterogeneous federated learning from coordinate matching to inter-class structural relations and reports up to 3.52% gains over prior methods.
Parameterized knowledge transfer for personalized federated learning
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.AI 2years
2026 2verdicts
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FedRio is a new federated framework that outperforms standard federated baselines in social bot detection accuracy and efficiency while staying competitive with centralized models under stronger privacy constraints.
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From Coordinate Matching to Structural Alignment: Rethinking Prototype Alignment in Heterogeneous Federated Learning
FedSAF shifts prototype alignment in heterogeneous federated learning from coordinate matching to inter-class structural relations and reports up to 3.52% gains over prior methods.
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FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation
FedRio is a new federated framework that outperforms standard federated baselines in social bot detection accuracy and efficiency while staying competitive with centralized models under stronger privacy constraints.