STAGE builds a shared semantic space through feature translation and controlled graph propagation to reduce semantic drift in multimodal federated graph learning, delivering state-of-the-art results with lower communication cost.
S2fgl: Spatial spectral federated graph learning
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PRISM proposes a topology-aware cross-modal imputation framework for client-level modality-deficient multimodal federated graph learning that improves deficient clients by 4.48% on average over baselines across six datasets.
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STAGE: Tackling Semantic Drift in Multimodal Federated Graph Learning
STAGE builds a shared semantic space through feature translation and controlled graph propagation to reduce semantic drift in multimodal federated graph learning, delivering state-of-the-art results with lower communication cost.
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PRISM: Topology-Aware Cross-Modal Imputation for Modality-Deficient Federated Graph Learning
PRISM proposes a topology-aware cross-modal imputation framework for client-level modality-deficient multimodal federated graph learning that improves deficient clients by 4.48% on average over baselines across six datasets.