Papers with Regulation-guided Tabular Anomaly Detection

1 papers
Integrating Data Validation with Large Language Models for Regulation-Guided Tabular Anomaly Detection (2026.acl-long)

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Challenge: Existing tabular anomaly detection methods focus on detecting anomalies based on data distribution without considering regulatory compliance.
Approach: They propose a task that leverages regulations to detect anomalies in tabular data . they also develop three new datasets to address this task .
Outcome: The proposed method outperforms baselines on three new datasets.

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