VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection

We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Syntax Tree AST structure, and code stylometry CStyle features. Prior work in code representation primarily leverages token-level models or full AST...

Focus on What Matters: Fisher-Guided Adaptive Multimodal Fusion for Vulnerability Detection

Software vulnerability detection is a critical task for securing software systems and can be formulated as a binary classification problem: given a code snippet, determine whether it contains a vulnerability. Existing multimodal approaches typically fuse Natural Code Sequence NCS representations...