SOURCE-LINKED INTELLIGENCE

Signed Graph Pre-Training and Prompt Learning

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Signed graphs arise in trust--distrust networks, financial correlation systems, biological interaction graphs, and many other domains in which edges can be positive or negative and may also be directed. While signed graph neural networks have improved task-specific learning, graph transfer learning on signed graphs remains underdeveloped. In this paper, we introduce TopoSIGN, a pioneer topology-guided graph pre-training and prompt learning framework for signed graphs. TopoSIGN combines a structural encoder built on the magnetic signed Laplacian with a novel persistent-homology branch that summ

Read original source ↗ Open in workspace

recordType

paper

region

Global