How Explainable Is Explainability? Towards Better Metrics for Explainable AI
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-44721-1_52
Reference37 articles.
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4. Szczepański, M., Choraś, M., Pawlicki, M., Kozik, R.: Achieving explainability of intrusion detection system by hybrid oracle-explainer approach. In: 2020 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE (2020)
5. Yu, J., Cristea, A.I., Harit, A., Sun, Z., Aduragba, O.T., Shi, L., Al Moubayed, N.: Interaction: a generative xai framework for natural language inference explanations. In: 2022 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE (2022)
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