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Author

Zhen Li

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Open access Oct 2026

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...

Jun-Yao Ye, Zhen Li, Xi Tang et al. · 0 citations
Open access Aug 2026

Semantically-Equivalent Transformations-Based Backdoor Attacks against Neural Code Models: Characterization and Mitigation

Semantically-Equivalent Transformation (SET)-based backdoor attacks are introduced, a new class of attacks that use semantics-preserving low-prevalence code transformations to generate stealthy triggers and are proposed as a framework for constructing and prioritizing such triggers.

Junyao Ye, Zhen Li, Xi Tang et al. · 0 citations

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