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Standard static analysis tools like CodeQL and Semgrep missed 100% of ground-truth autonomous vehicle software flaws that LLMs detected at a 76% rate, proving that LLMs excel at domain-specific cyber-physical logic bugs where rule-based methods entirely fail.
SLMs can match the performance of LLMs in detecting GNSS spoofing while being significantly more efficient for real-time applications in autonomous vehicles.