AFLiP: An Access-Recomputation Decoupling Framework for Efficient and Structure-Preserving GNN-based Link Prediction
This work realizes Access-Decoupled Recomputation as AFLiP, an efficient and structure-preserving framework for GNN-based link prediction, which matches or exceeds full-recomputation accuracy, while sampling and static reuse exhibit dataset-dependent degradation.