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Min-Soo Kim

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Book Open access Aug 2026

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.

Jeongmin Bae, Min-Soo Kim · 0 citations
Book Open access Aug 2026

AFLiP: An Access-Recomputation Decoupling Framework for Efficient and Structure-Preserving GNN-based Link Prediction

Many GNN-based link prediction models use a shared message-passing encoder to amortize node encoding across edges. However, in practice, neighborhood expansion makes the edge-level mini-batches approach near full-graph computation, weakening this benefit. Existing scalable techniques enable efficient mini-batch trainin...

Jeongmin Bae, Min-Soo Kim · 0 citations

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