A review of 80 studies from 2021-2025 on transformer-based software vulnerability detection identifies trends in architectures, datasets, and challenges such as data imbalance and interpretability.
Linevd: Statement- level vulnerability detection using graph neural networks, in: Pro- ceedings of the 19th international conference on mining software repositories, pp
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A systematic literature Review for Transformer-based Software Vulnerability detection
A review of 80 studies from 2021-2025 on transformer-based software vulnerability detection identifies trends in architectures, datasets, and challenges such as data imbalance and interpretability.