AAAI 2026technical0 citations

ARDiff: Anisotropic Residual Diffusion for Heterogeneous Graph Learning

Yong Chen, Li Li, Nannan Zong, Zhihui Liu, Song-Zhi Su

Abstract

Learning representations on graphs is foundational for many downstream tasks, and its synergy with diffusion models has emerged as a promising direction. However, diffusion-based methods for heterogeneous graphs remain underexplored, confronting two principal challenges: (1) The presence of noise and structural heterogeneity in graphs makes it challenging to accurately capture semantic transitions among diverse relation types. (2) The isotropic Gaussian noise used in forward diffusion fails to reflect graphs

BibTeX
@inproceedings{aaai2026_ardiffanisotropi,
  title = {ARDiff: Anisotropic Residual Diffusion for Heterogeneous Graph Learning},
  author = {Yong Chen and Li Li and Nannan Zong and Zhihui Liu and Song-Zhi Su},
  booktitle = {AAAI 2026},
  year = {2026}
}
ARDiff: Anisotropic Residual Diffusion for Heterogeneous Graph Learning · AAAI 2026