Shu-Lin Li

CID: Clean-Seed-Free Backdoor Defense via Counterfactual Invariance for Neural Code Models

Neural code models automate core software engineering tasks such as code classification and generation, but remain vulnerable to backdoor attacks. Existing defenses struggle with both injection-based and Semantically-Equivalent Transformation (SET)-based triggers and often require a trusted, pre-verified in-distributio...