BioDefect is a new dataset for defect detection in bioinformatics software that improves average F1-scores by 29.61% to 38.04% over existing datasets when evaluated on nine language models.
IEEE Transactions on Software Engineering50(8), 2163–2177 (2024)
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SAGE uses sparse autoencoders to boost vulnerability signals in LLMs, raising internal SNR 12.7x and delivering up to 318% MCC gains on vulnerability detection benchmarks.
Reproducibility study of Vul-RAG confirms original findings in a fully local open-weights setting but identifies a persistent performance plateau at approximately 0.30 pairwise accuracy across diverse recent open-weight LLMs.
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SAGE: Signal-Amplified Guided Embeddings for LLM-based Vulnerability Detection
SAGE uses sparse autoencoders to boost vulnerability signals in LLMs, raising internal SNR 12.7x and delivering up to 318% MCC gains on vulnerability detection benchmarks.