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标题为英语Discrete Diffusion for Large Graph Generation via Structural Candidate Restriction

Synthesizing realistic graphs at scale is vital when the graphs of interest are large and real-world samples are limited or access-sensitive. Diffusion-based generators have recently driven much of the progress, offering high modeling capacity, but most such methods have…

arXiv — cs.AI作者: Yassin Mohamadi, Zeno Geradts, Marcel Worring2026年10月6日 (10月6日)
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  • Synthesizing realistic graphs at scale is vital when the graphs of interest are large and real-world samples are limited or access-sensitive
  • Diffusion-based generators have recently driven much of the progress, offering high modeling capacity, but most such methods have…
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Discrete Diffusion for Large Graph Generation via Structural Candidate Restriction

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