3 citations · 9 across the 10 of their papers we have counts for
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cs.AI2023★ 2 cited
Advancing Post Hoc Case Based Explanation with Feature Highlighting
Eoin Kenny, Eoin Delaney, Mark Keane
Explainable AI (XAI) has been proposed as a valuable tool to assist in downstream tasks involving human and AI collaboration. Perhaps the most psychologically valid XAI techniques…
cs.AI2023★ 1 cited
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals
Greta Warren, Mark T. Keane, Christophe Gueret +1
Counterfactual explanations are an increasingly popular form of post hoc explanation due to their (i) applicability across problem domains, (ii) proposed legal compliance (e.g., wi…
cs.AI2023
Even if Explanations: Prior Work, Desiderata & Benchmarks for Semi-Factual XAI
Saugat Aryal, Mark T Keane
Recently, eXplainable AI (XAI) research has focused on counterfactual explanations as post-hoc justifications for AI-system decisions (e.g. a customer refused a loan might be told:…