5 papers
VulValidate: Auditing Function-Level Vulnerability Labels with Executable Evidence
Leizhen Zhang, Sheng Chen
Reliable learning-based vulnerability detection requires high-quality labels, yet datasets built from vulnerability-fixing commits may label functions as vulnerable simply because…
Satisfiability Solving with LLMs: A Matched-Pair Evaluation of Reasoning Capability
Leizhen Zhang, Shuhan Chen, Sheng Chen
Large language models (LLMs) are increasingly used for tasks that implicitly reduce to Boolean satisfiability (SAT), yet their reasoning ability on SAT remains unclear. We present…
BLIA: Detect model memorization in binary classification model through passive Label Inference attack
Mohammad Wahiduzzaman Khan, Sheng Chen, Ilya Mironov +2
Model memorization has implications for both the generalization capacity of machine learning models and the privacy of their training data. This paper investigates label memorizati…
Fairness-Aware Streaming Feature Selection with Causal Graphs
Leizhen Zhang, Lusi Li, Di Wu +2
Its crux lies in the optimization of a tradeoff between accuracy and fairness of resultant models on the selected feature subset. The technical challenge of our setting is twofold:…
Uncertainty Quantification in Table Structure Recognition
Kehinde Ajayi, Leizhen Zhang, Yi He +1
Quantifying uncertainties for machine learning models is a critical step to reduce human verification effort by detecting predictions with low confidence. This paper proposes a met…