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Improving Federated Graph Recommendation with Semantic Guidance
Graph-based recommendation models effectively capture high-order collaborative signals from user--item interaction graphs. Federated learning (FL) enables privacy-preserving training across distributed clients. However, directly aggregating graph representations under FL is challenging: locally lear
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