4 citations · 6 across the 9 of their papers we have counts for
Showing 2024 · cs.LGShow all
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cs.LG2024
UniGAD: Unifying Multi-level Graph Anomaly Detection
Yiqing Lin, Jianheng Tang, Chenyi Zi +3
Graph Anomaly Detection (GAD) aims to identify uncommon, deviated, or suspicious objects within graph-structured data. Existing methods generally focus on a single graph object typ…
cs.LG2024★ 4 cited
ProG: A Graph Prompt Learning Benchmark
Chenyi Zi, Haihong Zhao, Xiangguo Sun +3
Artificial general intelligence on graphs has shown significant advancements across various applications, yet the traditional 'Pre-train & Fine-tune' paradigm faces inefficiencies…
cs.LG2024★ 2 cited
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment
Haihong Zhao, Chenyi Zi, Yang Liu +3
Anomaly detection (AD) plays a pivotal role in numerous web-based applications, including malware detection, anti-money laundering, device failure detection, and network fault anal…