Chengyu Yao — accepted AI-conference papers

2026

Exploring Motif-based Heterogeneous Graph Learning for ReDoS Detection

Hong Huang, Chengyu Yao, Rongchen Li, Weihao Su, Chengyao Peng, Haiming Chen +1

ICML 2026poster

Regular expressions (regexes) frequently exhibit super-linear worst-case behavior in regex engines, exposing software to Regex Denial-of-Service (ReDoS) attacks. Detecting such vulnerabilities is challenging, especially for extended features such as lookarounds and backreferences: existing static ap…

Cited by 0 Source ↗Scholar ↗

2024

Rethinking Causal Relationships Learning in Graph Neural Networks

Hang Gao, Chengyu Yao, Jiangmeng Li, Lingyu Si, Yifan Jin, Fengge Wu +2

AAAI 2024technical

Graph Neural Networks (GNNs) demonstrate their significance by effectively modeling complex interrelationships within graph-structured data. To enhance the credibility and robustness of GNNs, it becomes exceptionally crucial to bolster their ability to capture causal relationships. However, despite…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗