FedUTR fuses textual item representations with user interactions via fusion and adaptation modules to improve federated recommendations under high sparsity, with up to 59% gains over baselines and convergence guarantees.
Lightfr: Lightweight federated recommendation with privacy-preserving matrix factorization,
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FedUTR: Federated Recommendation with Augmented Universal Textual Representation for Sparse Interaction Scenarios
FedUTR fuses textual item representations with user interactions via fusion and adaptation modules to improve federated recommendations under high sparsity, with up to 59% gains over baselines and convergence guarantees.