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Controllable graph diffusion for community search

delete2026-07-28
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PRE
AI
T
Tiesunlong Shen
J
Jin Wang *
L
Liang-Chih Yu *
王津 cover
王津 (Jin Wang)
R
Rui Mao
E
Erik Cambria
DOI:10.1016/j.inffus.2026.104655delete
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Abstract

Abstract

En 中文
• CGD is a controllable graph diffusion model that recasts community search as a community generation task. • A discrete diffusion process preserves the original graph topology, which continuous graph diffusion models cannot retain. • A copilot network handles attributed community search without retraining the full model. • Experiments on nine real-world graph datasets show CGD outperforms state-of-the-art community search baselines.
Keywords:
Diffusion
Graph pattern recognition
Graph neural network

Journal

Information Fusion cover
Information Fusion
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15.5
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Yuan Ze University
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National University of Singapore
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