1 citations · 1 across the 3 of their papers we have counts for
4 papers
AEGIS: From Clues to Verdicts -- Graph-Guided Deep Vulnerability Reasoning via Dialectics and Meta-Auditing
Sen Fang, Weiyuan Ding, Zhezhen Cao +2
Large Language Models (LLMs) are increasingly adopted for vulnerability detection, yet their reasoning remains fundamentally unsound. We identify a root cause shared by both major…
Understanding Privacy Risks in Code Models Through Training Dynamics: A Causal Approach
Hua Yang, Alejandro Velasco, Sen Fang +2
Large language models for code (LLM4Code) have greatly improved developer productivity but also raise privacy concerns due to their reliance on open-source repositories containing…
Smaller = Weaker? Benchmarking Robustness of Quantized LLMs in Code Generation
Sen Fang, Weiyuan Ding, Antonio Mastropaolo +1
Quantization has emerged as a mainstream method for compressing Large Language Models (LLMs), reducing memory requirements and accelerating inference without architectural modifica…
EVALOOOP: A Self-Consistency-Centered Framework for Assessing Large Language Model Robustness in Programming
Sen Fang, Weiyuan Ding, Mengshi Zhang +2
Evaluating the programming robustness of large language models (LLMs) is paramount for ensuring their reliability in AI-based software development. However, adversarial attacks exh…