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Source: AuthorWhat are LLM Evaluation Metrics?Large Language Models (LLMs) have revolutionized the field of Natural Language Processing (NLP) due to their ability to understand and generate human language with remarkable proficiency. These models like GPT-4, BERT, T5, etc. are being utilized in a variety of applications ranging from automated text generation and translation to conversational agents, and content recommendation systems. Evaluating these LLMs has become critical to ensure their effectiveness and reliability.Evaluation with the help of various evaluation metrics helps developers understand how a model is performing in different contexts and tasks. Moreover, effective evaluation plays a pivotal role in…

arXiv:2408.03475v1 Announce Type: new Abstract: An emerging topic in large language models (LLMs) is their application to time series forecasting, characterizing mainstream and patternable characteristics of time series. A relevant but rarely explored and more challenging question is whether LLMs can detect and explain time series anomalies, a critical task across various real-world applications. In this paper, we investigate the capabilities of LLMs, specifically GPT-4 and LLaMA3, in detecting and explaining anomalies in time series. Our studies reveal that: 1) LLMs cannot be directly used for time series anomaly detection. 2) By designing prompt strategies such as in-context learning and…