AINeutralarXiv – CS AI · Jun 236/10
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CQD-SHAP: Explainable Complex Query Answering via Shapley Values
Researchers introduce CQD-SHAP, a framework that explains how neural models answer complex queries over incomplete knowledge graphs by computing the contribution of each query component using Shapley values from game theory. This approach addresses the black-box nature of existing complex query answering methods and demonstrates consistent effectiveness across multiple datasets.