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    Efficient anomaly detection in tabular cybersecurity data using large language models by Xiaoyong Zhao, Xingxin Leng, Lei Wang, Ningning Wang, Yanqiong Liu

    Published 2025-01-01
    “…To address these limitations, this paper presents an innovative method for tabular data anomaly detection based on large language models, called “Tabular Anomaly Detection via Guided Prompts” (TAD-GP). This approach utilizes a 7-billion-parameter open-source model and incorporates strategies such as data sample introduction, anomaly type recognition, chain-of-thought reasoning, multi-turn dialogue, and key information reinforcement. …”
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