3 papers
cs.CR2026
Learning to Generate Secure Code via Token-Level Rewards
Jiazheng Quan, Xiaodong Li, Bin Wang +5
Large language models (LLMs) have demonstrated strong capabilities in code generation, yet they remain prone to producing security vulnerabilities. Existing approaches commonly suf…
cs.CR2025
Reflection-Driven Control for Trustworthy Code Agents
Bin Wang, Jiazheng Quan, Xingrui Yu +3
Contemporary large language model (LLM) agents are remarkably capable, but they still lack reliable safety controls and can produce unconstrained, unpredictable, and even actively…
cs.SE2025
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Keke Lian, Bin Wang, Lei Zhang +19
The increasing adoption of large language models (LLMs) in software engineering necessitates rigorous security evaluation of their generated code. However, existing benchmarks ofte…