A meta-prompt and hierarchical detection framework automates LLM red-teaming, achieving 3.9 times higher vulnerability discovery rate than manual methods with 89% accuracy on GPT-OSS-20B.
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Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models
A meta-prompt and hierarchical detection framework automates LLM red-teaming, achieving 3.9 times higher vulnerability discovery rate than manual methods with 89% accuracy on GPT-OSS-20B.