arXiv cs.LG
· Papers
Frequency-Corrupt Based Graph Self-Supervised Learning
arXiv:2604.15699v2 Announce Type: replace Abstract: Graph self-supervised learning can reduce the need for labeled graph data and has been widely used in recommendation, social networks, and other web applications. However, existing methods often underuse high-frequency signals and may overfit to specific local pattern