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arXiv (Cornell University)
Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
June 2025 • Shova Kuikel, Aritran Piplai, Palvi Aggarwal
Phishing attacks remain one of the most prevalent and persistent cybersecurity threat with attackers continuously evolving and intensifying tactics to evade the general detection system. Despite significant advances in artificial intelligence and machine learning, faithfully reproducing the interpretable reasoning with classification and explainability that underpin phishing judgments remains challenging. Due to recent advancement in Natural Language Processing, Large Language Models (LLMs) show a promising direct…
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