AI RESEARCH
HOG-Diff: Higher-Order Guided Diffusion for Graph Generation
arXiv CS.AI
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ArXi:2502.04308v3 Announce Type: replace-cross Graph generation is a critical yet challenging task, as empirical analyses require a deep understanding of complex, non-Euclidean structures. Diffusion models have recently made significant advances in graph generation, but these models are typically adapted from image generation frameworks and overlook inherent higher-order topology, limiting their ability to capture graph topology.