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Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals
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., with GDPR), and (iii) reliance on the contrastive nature of human explanation.
Background Knowledge Injection for Interpretable Sequence Classification
Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols.
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