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

ArXi:2601.02438v3 Announce Type: replace-cross Software vulnerability detection can be formulated as a binary classification problem that determines whether a given code snippet contains security defects. Existing multimodal methods typically fuse Natural Code Sequence (NCS) representations extracted by pretrained models with Code Property Graph (CPG) representations extracted by graph neural networks, under the implicit assumption that