Subgraph Filtering for Fair Graph Neural Networks
Subgraph Filtering for Fair Graph Neural Networks is proposed, a lightweight and architecture-agnostic framework that mitigates structural bias at its source and achieves consistent fairness improvements while maintaining competitive predictive performance, leading to a better fairness--accuracy trade-off than recent fairness-aware GNN baselines.