How Case Based Reasoning Explained Neural Networks: An XAI Survey of Post-Hoc Explanation-by-Example in ANN-CBR Twins

International Conference on Case-Based Reasoning (ICCBR), 2019

17 May 2019

Mark T. Keane

Eoin M. Kenny

ArXiv (abs)PDF HTML

Papers citing "How Case Based Reasoning Explained Neural Networks: An XAI Survey of Post-Hoc Explanation-by-Example in ANN-CBR Twins"

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Explainable deep learning improves human mental models of self-driving cars

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24 Dec 2025

Prototype-Based Methods in Explainable AI and Emerging Opportunities in the Geosciences

Anushka Narayanan

Karianne J. Bergen

379

22 Oct 2024

Using Part-based Representations for Explainable Deep Reinforcement Learning

Manos Kirtas

Konstantinos Tsampazis

Loukia Avramelou

Nikolaos Passalis

Anastasios Tefas

268

21 Aug 2024

The AI-DEC: A Card-based Design Method for User-centered AI Explanations

291

26 May 2024

CoProNN: Concept-based Prototypical Nearest Neighbors for Explaining Vision Models

Teodor Chiaburu

Frank Haußer

Felix Bießmann

310

23 Apr 2024

Model-agnostic Body Part Relevance Assessment for Pedestrian Detection

228

27 Nov 2023

Interpretable by Design: Wrapper Boxes Combine Neural Performance with Faithful Attribution of Model Decisions to Training DataBlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP), 2023

Yiheng Su

Junyi Jessy Li

Matthew Lease

AAML FAtt

261

15 Nov 2023

Robust Text Classification: Analyzing Prototype-Based NetworksConference on Empirical Methods in Natural Language Processing (EMNLP), 2023

337

11 Nov 2023

Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of ExamplesNeural Information Processing Systems (NeurIPS), 2023

438

11 Oct 2023

What's meant by explainable model: A Scoping Review

Mallika Mainali

Rosina O. Weber

XAI

343

18 Jul 2023

XAIR: A Framework of Explainable AI in Augmented RealityInternational Conference on Human Factors in Computing Systems (CHI), 2023

Xuhai Xu

Anna Yu

Tanya R. Jonker

Kashyap Todi

...

206

28 Mar 2023

Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations DifferArtificial Intelligence (AI), 2022

330

16 Dec 2022

Interpretable ML for Imbalanced Data

296

15 Dec 2022

Case-Based Inverse Reinforcement Learning Using Temporal CoherenceInternational Conference on Case-Based Reasoning (ICCBR), 2022

Claudia Linnhoff-Popien

174

12 Jun 2022

Explaining Latent Representations with a Corpus of ExamplesNeural Information Processing Systems (NeurIPS), 2021

208

28 Oct 2021

Informed Machine Learning for Improved Similarity Assessment in Process-Oriented Case-Based Reasoning

Maximilian Hoffmann

Ralph Bergmann

129

30 Jun 2021

Explainable AI, but explainable to whom?

Julie Gerlings

Millie Søndergaard Jensen

Arisa Shollo

231

10 Jun 2021

Mitigating belief projection in explainable artificial intelligence via Bayesian TeachingScientific Reports (Sci Rep), 2021

Scott Cheng-Hsin Yang

Wai Keen Vong

Ravi B. Sojitra

Tomas Folke

Patrick Shafto

271

07 Feb 2021

Qualitative Investigation in Explainable Artificial Intelligence: A Bit More Insight from Social Science

Adam J. Johs

Denise E. Agosto

Rosina O. Weber

313

13 Nov 2020

Instance-based Counterfactual Explanations for Time Series Classification

258

122

28 Sep 2020

On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep LearningAAAI Conference on Artificial Intelligence (AAAI), 2020

Eoin M. Kenny

Mark T. Keane

344

119

10 Sep 2020

The Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2019

Mark T. Keane

Eoin M. Kenny

280

20 May 2019