Machine Learning Performance vs Explanation Quality: Can We Have the Best of Both Worlds?

Authors

Olivier Teste (ORCID: https://orcid.org/0000-0003-0338-9886)
André Péninou (ORCID: https://orcid.org/0000-0001-6387-0079)
Moncef Garouani (ORCID: https://orcid.org/0000-0003-2528-441X)
Véronne Yepmo
Julien Aligon

Publication Details

Journal: HAL (Le Centre pour la Communication Scientifique Directe)
Published: 2026-06-09
Primary Topic: Explainable Artificial Intelligence (XAI)
Type: article
Field-Weighted Citation Impact: 0.00

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article

Machine Learning Performance vs Explanation Quality: Can We Have the Best of Both Worlds?

Olivier Teste, André Péninou, Moncef Garouani, Véronne Yepmo et al.

Jun 9, 2026

HAL (Le Centre pour la Communication Scientifique Directe)

Explainable Artificial Intelligence (XAI)

article

Machine Learning Performance vs Explanation Quality: Can We Have the Best of Both Worlds?

Olivier Teste, André Péninou, Moncef Garouani, Véronne Yepmo, Julien Aligon

June 9, 2026article en

Abstract

No abstract available for this paper.

HAL (Le Centre pour la Communication Scientifique Directe)

Openalex Percentile: Top 7%

Explainable Artificial Intelligence (XAI)

OpenAlex

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Machine Learning Performance vs Explanation Quality: Can We Have the Best of Both Worlds? — Olivier Teste, André Péninou, et al. · HAL (Le Centre pour la Communication Scientifique Directe) (2026) | TGRS Research Map | TGRS