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Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective

Neural Information Processing Systems

Graph Collaborative Filtering (GCF) is widely used in personalized recommendation systems. However, GCF suffers from a fundamental problem where features tend to occupy the embedding space inefficiently (by spanning only a low-dimensional subspace).