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Author

Jiancu Chen

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Jul 2026

Towards Faithful Graph Explanations with Synergistic Edge Effects via Granular Balls

This work proposes SeeExplainer, a parameter-free explainer to interpret graph neural networks, and introduces a granular-ball graph refinement mechanism that decomposes a graph into several disjoint granular-balls with no fixed size, and utilizes them as nodes to construct a structural graph.

Jian-Cu Chen, Shuyin Xia, Guan Wang et al. · 0 citations

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