Efficient Software Vulnerability Detection Using Transformer-based Models

ArXi:2604.00112v1 Announce Type: cross Detecting software vulnerabilities is critical to ensuring the security and reliability of modern computer systems. Deep neural networks have shown promising results on vulnerability detection, but they lack the capability to capture global contextual information on vulnerable code. To address this limitation, we explore the application of transformers for C/C++ vulnerability detection.