AI RESEARCH
Towards One-for-All Anomaly Detection for Tabular Data
arXiv CS.LG
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ArXi:2603.14407v1 Announce Type: new Tabular anomaly detection (TAD) aims to identify samples that deviate from the majority in tabular data and is critical in many real-world applications. However, existing methods follow a ``one model for one dataset (OFO)'' paradigm, which relies on dataset-specific