Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review

The systematic literature review (SLR) titled "Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review" provides an in-depth analysis of the role and efficacy of Large Language Models (LLMs) in the domains of forecasting and anomaly detection. The review meticulously examines the current research landscape, identifies inherent challenges, and explores future directions for the integration of LLMs in these critical fields. LLMs, such as BERT, GPT-3, and GPT-4, have shown substantial potential in parsing and analyzing extensive datasets, thereby enabling the identification of patterns, prediction of future events, and detection of anomalous behaviors across various domains.