2 papers
cs.CR2026
FraudFox: Adaptable Fraud Detection in the Real World
Matthew Butler, Yi Fan, Christos Faloutsos
The proposed method (FraudFox) provides solutions to adversarial attacks in a resource constrained environment. We focus on questions like the following: How suspicious is `Smith',…
cs.LG2025
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning
Jing Zhu, Xiang Song, Vassilis N. Ioannidis +2
How can we enhance the node features acquired from Pretrained Models (PMs) to better suit downstream graph learning tasks? Graph Neural Networks (GNNs) have become the state-of-the…