1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.SE2026
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…
cs.SE2025★ 1 cited
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…
cs.SE2025
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…