The Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep Learning

20 May 2019

Papers citing "The Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep Learning"

6 / 6 papers shown

Title
Natural Example-Based Explainability: a Survey Antonin Poché Lucas Hervier M. Bakkay XAI 33 12 0 05 Sep 2023
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification Adrien Bennetot Gianni Franchi Javier Del Ser Raja Chatila Natalia Díaz Rodríguez AAML 37 28 0 26 Sep 2022
Explaining Latent Representations with a Corpus of Examples Jonathan Crabbé Zhaozhi Qian F. Imrie M. Schaar FAtt 18 37 0 28 Oct 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 32 146 0 26 Feb 2021
Play MNIST For Me! User Studies on the Effects of Post-Hoc, Example-Based Explanations & Error Rates on Debugging a Deep Learning, Black-Box Classifier Courtney Ford Eoin M. Kenny Mark T. Keane 23 6 0 10 Sep 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 41 6,125 0 22 Oct 2019