From Lab to Reality: A Practical Evaluation of Deep Learning Models and LLMs for Vulnerability Detection

Excerpt

arXiv:2512.10485v3 Announce Type: replace-cross Abstract: Vulnerability detection methods based on deep learning (DL) have shown strong performance on benchmark datasets, yet their real-world effectiveness remains underexplored. Recent work suggests that graph neural network-based and transformer-based models, including large language models (LLMs), yield promising results when evaluated on curated benchmark datasets. These datasets are typically characterized by similar data distributions and m