AI RESEARCH
Hierarchical Discrete Flow Matching for Graph Generation
arXiv CS.LG
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ArXi:2604.00236v1 Announce Type: new Denoising-based models, including diffusion and flow matching, have led to substantial advances in graph generation. Despite this progress, such models remain constrained by two fundamental limitations: a computational cost that scales quadratically with the number of nodes and a large number of function evaluations required during generation. In this work, we