Author

Ru-Nang He

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#graph neural networks Book Open access Nov 2026

Capturing Collaborative Structure in Graph Anomaly Detection by MoE-Gated Neural Common Neighbor

In real-world graphs, anomalies usually exhibit collaborative structure, manifested as densely connected sub-graphs. Capturing multi-hop relationships is essential to identify and characterize the connections among these anomalous nodes. Existing graph anomaly detection (GAD) methods fail to capture such structures due...

Hui-Ling Peng, Tong-Ya Zheng, Ru-Nang He et al. · ACM International Conference... · 0 citations

#artificial intelligence Preprint Oct 2026

CryptoFlowBench: Benchmarking Multi-Hop Reasoning on Blockchains for Cryptocurrency Fund Tracing

This work proposes ChainSleuth, a graph-tool-augmented agent that iteratively reasons, invokes graph tools, and updates its tracing trajectory, enabling adaptive information acquisition and recovery from erroneous paths in multi-hop fund tracing.

Ru-Nang He, Tong-Ya Zheng, Jing-Yao Cao et al. · 0 citations