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Beijing Institute of Technology
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FedLAB achieves up to 7.53% improvement over existing methods while ensuring that multimodal graph knowledge remains traceable and privacy-preserving.
Missing modalities in federated learning can be effectively synthesized, leading to substantial performance gains in multimodal tasks.
PRISM boosts performance in modality-deficient federated graph learning by intelligently retrieving and integrating missing modalities from the entire federation.
