Reason to Explain: Interactive Contrastive Explanations (REASONX)

Author:

State LauraORCID,Ruggieri SalvatoreORCID,Turini FrancoORCID

Publisher

Springer Nature Switzerland

Reference53 articles.

1. Apt, K.: From Logic Programming to Prolog. Prentice Hall, London New York (1997)

2. Artelt, A., Vrachimis, S.G., Eliades, D.G., Polycarpou, M.M., Hammer, B.: One explanation to rule them all - ensemble consistent explanations. CoRR abs/2205.08974 (2022)

3. Balagopalan, A., Zhang, H., Hamidieh, K., Hartvigsen, T., Rudzicz, F., Ghassemi, M.: The road to explainability is paved with bias: measuring the fairness of explanations. In: FAccT, pp. 1194–1206. ACM (2022)

4. Barocas, S., Selbst, A.D., Raghavan, M.: The hidden assumptions behind counterfactual explanations and principal reasons. In: FAT*, pp. 80–89. ACM (2020)

5. Beckh, K., et al.: Explainable machine learning with prior knowledge: an overview. CoRR abs/2105.10172 (2021)

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