Carpentier's motif-counting conjecture for community recovery in the stochastic block model

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Let G=(V,E)G=(V,E) be a connected graph with (v1,v2)∉E(v_1,v_2)\notin E. For any partition of VV into ℓ\ell groups in which v1v_1 and v2v_2 belong to the same group, let E≠E^{\neq} be the set of edges of EE joining distinct groups, and set

r:=∣E∣∣V∣−2.r:=\frac{|E|}{|V|-2}.

Carpentier's motif-counting conjecture. If

∣E≠∣≥r(ℓ−1),|E^{\neq}|\geq r(\ell-1),

for every such partition, and if q≍n−1/rq\asymp n^{-1/r} and λ≥log⁡q1−log⁡n(K)\lambda\geq_{\log}q^{1-\log_n(K)}, then the communities in the stochastic block model can be recovered by an algorithm based on PGP_G, the count of occurrences of the motif GG.

The conjecture identifies a sufficient combinatorial condition on a motif for counting its occurrences to achieve community recovery in the regime with more than n\sqrt n communities. The supplied text does not state whether this claim has been proved or disproved.

References

Primary source

Alexandra Carpentier, Christophe Giraud and Nicolas Verzelen, “Phase Transition for Stochastic Block Model with more than n Communities (II)”, arXiv:2511.21526 (2025).

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