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cs.AI2025
VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation
David Egea, Barproda Halder, Sanghamitra Dutta
Automated detection of vulnerabilities in source code is an essential cybersecurity challenge, underpinning trust in digital systems and services. Graph Neural Networks (GNNs) have…
cs.AI2025★ 2 cited
Demystifying the Accuracy-Interpretability Trade-Off: A Case Study of Inferring Ratings from Reviews
Pranjal Atrey, Michael P. Brundage, Min Wu +1
Interpretable machine learning models offer understandable reasoning behind their decision-making process, though they may not always match the performance of their black-box count…