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Qin, Q., & Merlo, E. (2025). Prune bias from the root: Bias removal and fairness estimation by pruning sensitive attributes in pre-trained DNN models. Information and Software Technology, 189, 107906 (12 pages). Lien externe
Qin, Q., Djian, B. P. P., Merlo, E., Li, H., & Gambs, S. (2025). Representation-based fairness evaluation and bias correction robustness assessment in neural networks. Information and Software Technology, 107876 (21 pages). Lien externe
Caumartin, G., Qin, Q., Chatragadda, S., Panjrolia, J., Li, H., & Elias Costa, D. (mars 2025). Exploring the Potential of Llama Models in Automated Code Refinement: A Replication Study [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2025), Montreal, QC, Canada. Lien externe
Qin, Q., Aghili, R., Li, H., & Merlo, E. (mars 2025). Preprocessing is All You Need: Boosting the Performance of Log Parsers with a General Preprocessing Framework [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2025), Montreal, QC, Canada. Lien externe
Qin, Q., Li, H., Merlo, E., & Lamothe, M. (avril 2025). Automated, Unsupervised, and Auto-Parameterized Inference of Data Patterns and Anomaly Detection [Communication écrite]. 47th International Conference on Software Engineering (ICSE 2025), Ottawa, ON, Canada. Lien externe
Qin, Q. (2025). Prune the Bias From the Root: Bias Removal and Fairness Estimation by Muting Sensitive Attributes in Pre-trained DNN Models [Ensemble de données]. Lien externe
Qin, Q., Li, H., Merlo, E., & Lamothe, M. (2025). Automated, Unsupervised, and Auto-parameterized Inference of Data Patterns and Anomaly Detection [Ensemble de données]. Lien externe
