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Research questionHow should ML vulnerability-detection benchmarks measure practical security capabilities beyond narrow binary function-level tasks?Machine-learning vulnerability detection research often concentrates on binary classification of C/C++ functions. Interlocking choices in datasets, formulations, baselines, and metrics can reinforce this narrow focus while leaving vulnerability types, language coverage, and practical usefulness underrepresented.
AI
Code Generation & Program Synthesis
Evaluation & Benchmarks
Machine Learning
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Technology
Latest papersRecent research connected to this question, newest first.Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain PointsThe source surveys 87 influential ML-based automated vulnerability-detection studies, identifies twelve causally interrelated pain points across the research pipeline, and examines AIxCC as a case study. Its evidence concerns research formulations and evaluations rather than a demonstrated replacement system.research paper · Sep 4, 2026
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