4 papers
The Explanation Game -- Rekindled (Extended Version)
Joao Marques-Silva, Xuanxiang Huang, Olivier Letoffe
Recent work demonstrated the existence of critical flaws in the current use of Shapley values in explainable AI (XAI), i.e. the so-called SHAP scores. These flaws are significant i…
Towards trustable SHAP scores
Olivier Letoffe, Xuanxiang Huang, Joao Marques-Silva
SHAP scores represent the proposed use of the well-known Shapley values in eXplainable Artificial Intelligence (XAI). Recent work has shown that the exact computation of SHAP score…
SHAP scores fail pervasively even when Lipschitz succeeds
Olivier Letoffe, Xuanxiang Huang, Joao Marques-Silva
The ubiquitous use of Shapley values in eXplainable AI (XAI) has been triggered by the tool SHAP, and as a result are commonly referred to as SHAP scores. Recent work devised examp…
From SHAP Scores to Feature Importance Scores
Olivier Letoffe, Xuanxiang Huang, Nicholas Asher +1
A central goal of eXplainable Artificial Intelligence (XAI) is to assign relative importance to the features of a Machine Learning (ML) model given some prediction. The importance…