3 papers
cs.LG2026
FoundAna: A GNN-assisted Foundation Model for Graph Anomaly Detection
Suprim Nakarmi, Chahana Dahal, Yue Zhao +2
Graph anomaly detection aims to identify graph structures (e.g., nodes, edges, or subgraphs) that deviate significantly from expected patterns, which supports critical applications…
cs.LG2026
Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding
An Huang, Junggab Son, Zuobin Xiong
Diffusion models have become the foundation of modern generative systems, with most research focusing primarily on improving generation efficiency and output quality. The timestep…
cs.LG2026
Fed-Listing: Federated Label Distribution Inference in Graph Neural Networks
Suprim Nakarmi, Junggab Son, Yue Zhao +1
Federated Graph Neural Networks (FedGNNs) facilitate collaborative learning across multiple clients with graph-structured data while preserving user privacy. However, emerging rese…