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View all- An SCao Y(2024)Counterfactual Explanation at Will, with Zero Privacy LeakageProceedings of the ACM on Management of Data10.1145/36549332:3(1-29)Online publication date: 30-May-2024
While counterfactuals have been extensively studied as an intuitive explanation of model predictions, they still have limited adoption in practice due to two obstacles: (a) They rely on excessive access to the model for explanation that the model owner ...
Vulnerability detection is crucial for ensuring the security and reliability of software systems. Recently, Graph Neural Networks (GNNs) have emerged as a prominent code embedding approach for vulnerability detection, owing to their ability to capture ...
The feature attribution-based explanation (FAE) methods, which indicate how much each input feature contributes to the model’s output for a given data point, are one of the most popular categories of explainable machine learning techniques. Although ...
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