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06/24/2022
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods
Machine Learning (ML) models now inform a wide range of human decisions,...
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05/07/2022
ConceptDistil: Model-Agnostic Distillation of Concept Explanations
Concept-based explanations aims to fill the model interpretability gap f...
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04/26/2021
Weakly Supervised Multi-task Learning for Concept-based Explainability
In ML-aided decision-making tasks, such as fraud detection or medical di...
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01/21/2021
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations
There have been several research works proposing new Explainable AI (XAI...
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11/27/2020