Yihan Liao
Orcid: 0000-0002-8002-9190
According to our database1,
Yihan Liao authored at least 17 papers
between 2024 and 2026.
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Collaborative distances:
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Bibliography
2026
UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems.
CoRR, April, 2026
Empirical Insights of Test Selection Metrics under Multiple Testing Objectives and Distribution Shifts.
CoRR, April, 2026
Trusting AI to detect AI? A systematic evaluation of the reliability and robustness of current AIGC detection tools for student academic work.
Comput. Educ., 2026
2025
SemiSMAC: A semi-supervised framework for log anomaly detection with automated hyperparameter tuning.
Inf. Softw. Technol., 2025
Advancing autonomous driving system testing: Demands, challenges, and future directions.
Inf. Softw. Technol., 2025
StuLAC: An Adaptive LLM-Driven Framework for Scalable Student Feedback Analysis in Software-Driven Educational Systems.
Proceedings of the 49th IEEE Annual Computers, Software, and Applications Conference, 2025
Beyond Log Parsers: A Scalable AI-Driven Framework for Efficient Log Anomaly Detection in Software Engineering.
Proceedings of the 49th IEEE Annual Computers, Software, and Applications Conference, 2025
Towards Lightweight LLM Software Solutions for InsurTech: A Framework for Scalable Question Answering Systems.
Proceedings of the 32nd Asia-Pacific Software Engineering Conference, 2025
Understanding Industrial Log Analysis: A Multi-Dataset Evaluation of Parsing and Anomaly Detection.
Proceedings of the 32nd Asia-Pacific Software Engineering Conference, 2025
Proceedings of the 32nd Asia-Pacific Software Engineering Conference, 2025
Proceedings of the 32nd Asia-Pacific Software Engineering Conference, 2025
Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems, 2025
2024
UniAda: Universal Adaptive Multiobjective Adversarial Attack for End-to-End Autonomous Driving Systems.
IEEE Trans. Reliab., December, 2024
Sci. Comput. Program., 2024
Delving into Parameter-Efficient Fine-Tuning in Code Change Learning: An Empirical Study.
Proceedings of the IEEE International Conference on Software Analysis, 2024
LLM-Based Class Diagram Derivation from User Stories with Chain-of-Thought Promptings.
Proceedings of the 48th IEEE Annual Computers, Software, and Applications Conference, 2024
Enhancing the Transferability of Adversarial Attacks for End-to-End Autonomous Driving Systems.
Proceedings of the 31st Asia-Pacific Software Engineering Conference, 2024