AI RESEARCH
SCGNN: Semantic Consistency enhanced Graph Neural Network Guided by Granular-ball Computing
arXiv CS.AI
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ArXi:2605.02617v2 Announce Type: new Capturing semantic consistency among nodes is crucial for effective graph representation learning. Existing approaches typically rely on $k$-nearest neighbors ($k$NN) or other node-level full search algorithms (FSA) to mine semantic relationships via exhaustive pairwise similarity computation, which suffer from high computational complexity and rigid neighbor selection, limiting scalability and