People › Hi Kuen Yu
About
Hi Kuen Yu is a PhD Student in the Department of Computer Science, City University of Hong Kong.
Research Interests
Publications (14)
- Where Do Expectations Diverge? an Empirical Analysis of Software Engineering Graduate Preparedness in Industry.
- LogMeta: A few-shot model-agnostic meta-learning framework for robust and adaptive log anomaly detection.
- Industrial log analysis revisited: A task-oriented evaluation of parsing and anomaly detection under real-world constraints.
- Improving anomaly detection in software logs through hybrid language modeling and reduced reliance on parser.
- Designing Psychologically Safe AI Tutors for Students: An Emotion-Aware Post-Hoc Intervention for LLM-Assisted Learning.
- At the point of risk: Can AI-assisted decision support reduce digital fraud vulnerability across age groups and scam types?
- Artifact-Constrained Agentic Testing for Black-Box System Testing under Actuarial and Regulatory Constraints.
- Fostering Critical Thinking by Integrating Case-Based Learning and Generative AI in a Closed-Loop Reflective Learning Environment
- Understanding Industrial Log Analysis: A Multi-Dataset Evaluation of Parsing and Anomaly Detection.
- Towards Lightweight LLM Software Solutions for InsurTech: A Framework for Scalable Question Answering Systems.
- StuLAC: An Adaptive LLM-Driven Framework for Scalable Student Feedback Analysis in Software-Driven Educational Systems.
- SemiRALD: A semi-supervised hybrid language model for robust Anomalous Log Detection.
- Beyond Log Parsers: A Scalable AI-Driven Framework for Efficient Log Anomaly Detection in Software Engineering.
- Unveiling Hidden Anomalies: Leveraging SMAC-LSTM for Enhanced Software Log Analysis.