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cs.CL2026
Towards Token-Level Text Anomaly Detection
Yang Cao, Bicheng Yu, Sikun Yang +2
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-l…
cs.CL2025
Text Anomaly Detection with Simplified Isolation Kernel
Yang Cao, Sikun Yang, Yujiu Yang +2
Two-step approaches combining pre-trained large language model embeddings and anomaly detectors demonstrate strong performance in text anomaly detection by leveraging rich semantic…
cs.CL2025
TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection
Yang Cao, Sikun Yang, Chen Li +5
Text anomaly detection is crucial for identifying spam, misinformation, and offensive language in natural language processing tasks. Despite the growing adoption of embedding-based…