works on

From the 1 of 5 linked papers with an AI index.

collaborators

5 papers

cs.AI2026

Evaluating and Improving Pedagogical Fit in LLM-Based AI Tutors with the Pedagogical Suitability Index

Benjamin Barlog, Hudson Craig, Zedong Peng

Large language models (LLMs) are increasingly used as AI tutors, but a correct answer is not always a pedagogically appropriate one. In classroom learning, effective help depends n…

cs.SE2026

When Post-Anchor Metrics Fail: Stabilization Regimes in AI-Evidence Open-Source Projects

Hudson Craig, Benjamin Barlog, Chenggang Wang +2

Repository mining studies increasingly analyze AI-evidence projects, yet it remains unclear how to measure whether architectural changes create deferred stabilization obligations.…

cs.CR2026

Cross-Cutting Security Analysis of LLM-Generated Code via Metamorphic Testing and Association Rule Mining

Zedong Peng, Chenggang Wang, Shangyue Zhu

The paper introduces a framework that combines security‑focused metamorphic testing with association rule mining to detect and analyze cross‑cutting vulnerabilities in code generat…

cs.SE2026

Failure-Aware Enhancements for Large Language Model (LLM) Code Generation: An Empirical Study on Decision Framework

Jianru Shen, Zedong Peng, Lucy Owen

Large language models (LLMs) show promise for automating software development by translating requirements into code. However, even advanced prompting workflows like progressive pro…

cs.SE2026

Advanced Vulnerability Scanning for Open Source Software: Detection and Mitigation of Log4j Vulnerabilities

Victor Wen, Zedong Peng

Automated detection of software vulnerabilities remains a critical challenge in software security. Log4j is an industrial-grade Java logging framework listed as one of the top 100…