Learning Generalizable Multimodal Representations for Software Vulnerability Detection

ArXi:2604.25711v1 Announce Type: cross Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capture developer intent. However, existing vulnerability detection methods mostly rely on single-modality code representations, overlooking the complementary semantic information embedded in comments and thus limiting their generalization across complex code structures and logical relationships.