Towards Token-Level Text Anomaly Detection
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The claim presents a new approach to text anomaly detection with some uncertainties about its implementation and effectiveness, but it is grounded in a technical and research context with emerging narratives rather than speculative intrigue.
Despite significant progress in text anomaly detection for web applications such as spam filtering and fake news detection, existing methods are fundamentally limited to document-level analysis, unable to identify which specific parts of a text are anomalous. We introduce token-level anomaly detection, a novel paradigm that enables fine-grained localization of anomalies within text. We formally define text anomalies at both document and token-levels, and propose a unified detection framework ...