Explaining GNN-based Recommendations in Logic

Summary: Introduce Makex, a logic-based explanation framework that discovers Rules for ExPlanations (REPs)—a graph pattern Q plus precondition predicates X→M(x,y)—to expose topology and feature dependencies driving GNN recommender outputs. Defines REPs via 1-WL, gives algorithms for global REP discovery and top-k local explanations, and reports superior fidelity, sparsity, and efficiency versus prior methods. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14231
Venue: VLDB
Year: 2025
Pagerank: 4.3441378e-05
Overall Rank: 9,400 | 34.61%
DOI: 10.14778/3712221.3712237

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,233	Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling	2026	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,190	word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data	2020	PODS	0.00013438056
1,867	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	0.00010272055
2,450	Functional Dependencies for Graphs	2016	SIGMOD	8.7882979e-05
2,527	Dependencies for Graphs	2017	PODS	8.5954406e-05
4,205	Association Rules with Graph Patterns	2015	VLDB	6.3597474e-05
6,153	On Data-Aware Global Explainability of Graph Neural Networks	2023	VLDB	5.1829258e-05
8,133	Towards Event Prediction in Temporal Graphs	2022	VLDB	4.5784634e-05
8,211	Capturing Associations in Graphs	2020	VLDB	4.5581054e-05
9,487	Making It Tractable to Catch Duplicates and Conflicts in Graphs	2023	SIGMOD	4.3341665e-05
11,209	Enriching Recommendation Models with Logic Conditions	2023	SIGMOD	4.1945683e-05

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