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DiFA: Dual Evidence Fusion and Aggregation for Token-Level Text Anomaly Detection
Text anomaly detection, the task of identifying text instances that deviate from normal language patterns, is crucial for language-driven applications. However, most existing methods can only perform document-level anomaly detection, making it hard to locate harmful phrases or support targeted preve
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