LLM-Powered Anomaly Detection in Longitudinal Texts via Functional PCA
Published:Dec 16, 2025 17:14
•1 min read
•ArXiv
Analysis
This research explores a novel application of Large Language Models (LLMs) in conjunction with Functional Principal Component Analysis (FPCA) for anomaly detection in sparse, longitudinal text data. The combination of LLMs for feature extraction and FPCA for identifying deviations presents a promising approach.
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Reference
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