AAAI 2026technical0 citations
Khan-GCL: Kolmogorov–Arnold Network Based Graph Contrastive Learning with Hard Negatives
Zihu Wang, Boxun Xu, Hejia Geng, Peng Li
Abstract
Graph contrastive learning (GCL) has demonstrated great promise for learning generalizable graph representations from unlabeled data. However, conventional GCL approaches face two critical limitations: (1) the restricted expressive capacity of multilayer perceptron (MLP) based encoders, and (2) suboptimal negative samples that either from random augmentations—failing to provide effective
BibTeX
@inproceedings{aaai2026_khangclkolmogoro,
title = {Khan-GCL: Kolmogorov–Arnold Network Based Graph Contrastive Learning with Hard Negatives},
author = {Zihu Wang and Boxun Xu and Hejia Geng and Peng Li},
booktitle = {AAAI 2026},
year = {2026}
}