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 quadratic computational…
By Yassin Mohamadi, Zeno Geradts, Marcel WorringarXiv - cs.AI
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Originally published by arXiv - cs.AI on Oct 6, 2026.
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