What is the percentage drop in zero-shot forecasting accuracy for Llama3 when evaluated on cross-domain time-s

Abstract

Abstract: Rapid developments in large language models (LLMs) have created new opportunities for their use in the energy sector, from forecasting renewable energy to power system operation and energy market analysis. These models help improve decision-making, anomaly detection, and optimization procedures in intricate energy systems by using vast amounts of structured and unstructured data. This study provides a comprehensive review of the LLM origins, evaluation, and fine-tuning techniques as well as their integration into energy systems, including their application in fault detection and diagnosis, ene

Research Question

What is the percentage drop in zero-shot forecasting accuracy for Llama3 when evaluated on cross-domain time-series anomalies compared to its in-domain performance?

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