46 citations · 130 across the 6 of their papers we have counts for
7 papers
Achieving Diversity in Counterfactual Explanations: a Review and Discussion
Thibault Laugel, Adulam Jeyasothy, Marie-Jeanne Lesot +2
In the field of Explainable Artificial Intelligence (XAI), counterfactual examples explain to a user the predictions of a trained decision model by indicating the modifications to…
Integrating Prior Knowledge in Post-hoc Explanations
Adulam Jeyasothy, Thibault Laugel, Marie-Jeanne Lesot +2
In the field of eXplainable Artificial Intelligence (XAI), post-hoc interpretability methods aim at explaining to a user the predictions of a trained decision model. Integrating pr…
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations
Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala +2
Post-hoc interpretability approaches have been proven to be powerful tools to generate explanations for the predictions made by a trained black-box model. However, they create the…
Issues with post-hoc counterfactual explanations: a discussion
Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala +1
Counterfactual post-hoc interpretability approaches have been proven to be useful tools to generate explanations for the predictions of a trained blackbox classifier. However, the…
Detecting Potential Local Adversarial Examples for Human-Interpretable Defense
Xavier Renard, Thibault Laugel, Marie-Jeanne Lesot +2
Machine learning models are increasingly used in the industry to make decisions such as credit insurance approval. Some people may be tempted to manipulate specific variables, such…
Defining Locality for Surrogates in Post-hoc Interpretablity
Thibault Laugel, Xavier Renard, Marie-Jeanne Lesot +2
Local surrogate models, to approximate the local decision boundary of a black-box classifier, constitute one approach to generate explanations for the rationale behind an individua…