Mitigating Structural Overfitting: A Distribution-Aware Rectification Framework for Missing Feature Imputation

ArXi:2512.06356v3 Announce Type: replace Incomplete node features are ubiquitous in real-world scenarios such as user profiling and cold-start recommendation, which severely hinders the practical deployment of graph learning systems (e.g., GNNs). Existing solutions typically rely on diffusion-based structural smoothing (e.g., feature propagation) to impute missing values.