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Self-feeding can detect backdoors in fine-tuned LLMs with 92% precision, outperforming traditional methods and revealing hidden vulnerabilities in models that appear safe.
Achieving 99.60% accuracy with a model that requires only 2,370 FLOPS could redefine the landscape of IoT security solutions.