Open access
Jul 2026
LLM-AP: LLM-Based Anomaly Detection with Synthetic Time-Series Data Augmentation
This paper presents a method that addresses the imbalance between normal and anomaly data by transforming time-series data into a structured sentence format and using a large language model to generate and augment diverse anomaly scenarios.
Geunho Lee, Jieun Lee, Tae-yong Kim et al.
· Applied Sciences · 0 citations