bLIMEy: Surrogate Prediction Explanations Beyond LIME

29 October 2019

Kacper Sokol

Alexander Hepburn

Raúl Santos-Rodríguez

Peter A. Flach

FAtt

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Papers citing "bLIMEy: Surrogate Prediction Explanations Beyond LIME"

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Title
Which LIME should I trust? Concepts, Challenges, and Solutions Patrick Knab Sascha Marton Udo Schlegel Christian Bartelt FAtt 40 0 0 31 Mar 2025
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 45 0 0 29 Oct 2024
ContextCite: Attributing Model Generation to Context Benjamin Cohen-Wang Harshay Shah Kristian Georgiev Aleksander Madry LRM 41 19 0 01 Sep 2024
CHILLI: A data context-aware perturbation method for XAI Saif Anwar Nathan Griffiths A. Bhalerao T. Popham 44 0 0 10 Jul 2024
What Does Evaluation of Explainable Artificial Intelligence Actually Tell Us? A Case for Compositional and Contextual Validation of XAI Building Blocks Kacper Sokol Julia E. Vogt 37 11 0 19 Mar 2024
Identification, explanation and clinical evaluation of hospital patient subtypes Enrico Werner J. N. Clark R. Bhamber M. Ambler Christopher P Bourdeaux Alexander Hepburn C. McWilliams Raúl Santos-Rodríguez 16 3 0 19 Jan 2023
Local Interpretable Model Agnostic Shap Explanations for machine learning models P. Aditya M. Pal FAtt 36 6 0 10 Oct 2022
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components Kacper Sokol Alexander Hepburn Raúl Santos-Rodríguez Peter A. Flach 42 8 0 08 Sep 2022
Sampling Based On Natural Image Statistics Improves Local Surrogate Explainers Ricardo Kleinlein Alexander Hepburn Raúl Santos-Rodríguez Fernando Fernández-Martínez AAML FAtt 27 2 0 08 Aug 2022
Integrating Prior Knowledge in Post-hoc Explanations Adulam Jeyasothy Thibault Laugel Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki 17 6 0 25 Apr 2022
Datamodels: Predicting Predictions from Training Data Andrew Ilyas Sung Min Park Logan Engstrom Guillaume Leclerc A. Madry TDI 52 131 0 01 Feb 2022
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence Kacper Sokol Peter A. Flach 41 21 0 29 Dec 2021
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach Jonas Schulz Rafael Poyiadzi Raúl Santos-Rodríguez 34 7 0 17 Nov 2021
Understanding surrogate explanations: the interplay between complexity, fidelity and coverage Rafael Poyiadzi X. Renard Thibault Laugel Raúl Santos-Rodríguez Marcin Detyniecki 13 6 0 09 Jul 2021
A Review of Explainable Artificial Intelligence in Manufacturing G. Sofianidis Jože M. Rožanec Dunja Mladenić D. Kyriazis 25 17 0 05 Jul 2021
Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception Alexander Hepburn Raúl Santos-Rodríguez FAtt 21 4 0 22 Feb 2021
Reviewing the Need for Explainable Artificial Intelligence (xAI) Julie Gerlings Arisa Shollo Ioanna D. Constantiou 22 73 0 02 Dec 2020
Interpretable Representations in Explainable AI: From Theory to Practice Kacper Sokol Peter A. Flach 9 9 0 16 Aug 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 29 162 0 11 Aug 2020
On quantitative aspects of model interpretability An-phi Nguyen María Rodríguez Martínez 24 114 0 15 Jul 2020
One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency Kacper Sokol Peter A. Flach 6 171 0 27 Jan 2020
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches Kacper Sokol Peter A. Flach XAI 19 299 0 11 Dec 2019
FACE: Feasible and Actionable Counterfactual Explanations Rafael Poyiadzi Kacper Sokol Raúl Santos-Rodríguez T. D. Bie Peter A. Flach 11 365 0 20 Sep 2019
FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency Kacper Sokol Raúl Santos-Rodríguez Peter A. Flach 22 37 0 11 Sep 2019