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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

On the failings of Shapley values for explainability
Xuanxiang Huang, João Marques‐Silva
International Journal of Approximate Reasoning (2024) Vol. 171, pp. 109112-109112
Closed Access | Times Cited: 20

Showing 20 citing articles:

Guaranteeing Correctness in Black-Box Machine Learning: A Fusion of Explainable AI and Formal Methods for Healthcare Decision-Making
Nadia Khan, Muhammad Nauman, Ahmad Almadhor, et al.
IEEE Access (2024) Vol. 12, pp. 90299-90316
Open Access | Times Cited: 9
Combining SHAP-Driven Co-clustering and Shallow Decision Trees to Explain XGBoost
Ruggero G. Pensa, Anton Crombach, Sergio Peignier, et al.
Lecture notes in computer science (2025), pp. 369-384
Open Access
The Right to an Explanation Under the GDPR and the AI Act
Bjørn Aslak Juliussen
Lecture notes in computer science (2025), pp. 184-197
Closed Access
A systematic review of machine learning applications in predicting opioid associated adverse events
Carlos R. Ramírez Medina, Jose Benitez-Aurioles, David Jenkins, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access
Iaml: A Modular and Explainable Automl Framework for High-Performance on Tabular Data
Rudy Merieux, Hugo RUELLET, Robin BOURACHOT, et al.
(2025)
Closed Access
Oxidation Stability of Hydrocarbons: A Machine-Learning-Based Study
Adrian Venegas-Reynoso, Benoît Creton, Lucia Giarracca, et al.
Energy & Fuels (2025) Vol. 39, Iss. 9, pp. 4361-4373
Closed Access
Explaining quantum circuits with Shapley values: towards explainable quantum machine learning
Raoul Heese, Thore Gerlach, Sascha Mücke, et al.
Quantum Machine Intelligence (2025) Vol. 7, Iss. 1
Open Access
Breast cancer prediction based on gene expression data using interpretable machine learning techniques
Gabriel Kallah-Dagadu, Mohanad Mohammed, Justine B. Nasejje, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Reevaluating Feature Importance in Machine Learning: Concerns Regarding SHAP Interpretations in the Context of the EU Artificial Intelligence Act
Yoshiyasu Takefuji
Water Research (2025), pp. 123514-123514
Closed Access
RealExp: Decoupling correlation bias in Shapley values for faithful model interpretations
Wendong Jiang, Chih‐Yung Chang, Show-Jane Yen, et al.
Information Processing & Management (2025) Vol. 62, Iss. 4, pp. 104153-104153
Closed Access
An urgent call for robust statistical methods in reliable feature importance analysis across machine learning
Yoshiyasu Takefuji
Journal of Catalysis (2025), pp. 116098-116098
Closed Access
Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group
Ismaïl Baaj, Zied Bouraoui, Antoine Cornuéjols, et al.
International Journal of Approximate Reasoning (2024) Vol. 171, pp. 109206-109206
Open Access | Times Cited: 2
Using Narrative Disclosures to Predict Tax Outcomes
Olga Bogachek, Antonio De Vito, Paul Demeré, et al.
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 5
Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning
Davood Pirayesh Neghab, Mücahit Çevik, M.I.M. Wahab, et al.
Computational Economics (2024)
Closed Access | Times Cited: 1
Conditional Feature Selection: Evaluating Model Averaging When Selecting Features with Shapley Values
Florian Huber, Volker Steinhage
Geomatics (2024) Vol. 4, Iss. 3, pp. 286-310
Open Access | Times Cited: 1
The application of eXplainable artificial intelligence in studying cognition: A scoping review
Abu Bakar Shakran Bin Mahmood, Colin Teo, Jeremy Sim, et al.
Ibrain (2024)
Open Access | Times Cited: 1
Logic-Based Explainability: Past, Present and Future
João Marques‐Silva
Lecture notes in computer science (2024), pp. 181-204
Closed Access | Times Cited: 1
Feature Identification Using Interpretability Machine Learning Predicting Risk Factors for Disease Severity of In-Patients with COVID-19 in South Florida
Debarshi Datta, Subhosit Ray, Laurie A. Martinez, et al.
Diagnostics (2024) Vol. 14, Iss. 17, pp. 1866-1866
Open Access
Competing narratives in AI ethics: a defense of sociotechnical pragmatism
David Watson, Jakob Mökander, Luciano Floridi
AI & Society (2024)
Open Access
Error Analysis of Shapley Value-Based Model Explanations: An Informative Perspective
Ningsheng Zhao, Jia Yuan Yu, Krzysztof Dzięciołowski, et al.
Lecture notes in computer science (2024), pp. 29-48
Closed Access
Exploring accuracy and interpretability trade-off in tabular learning with novel attention-based models
Kodjo Mawuena Amekoe, Hanane Azzag, Zaineb Chelly Dagdia, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 30, pp. 18583-18611
Closed Access
A comprehensive survey and classification of evaluation criteria for trustworthy artificial intelligence
Louise McCormack, Malika Bendechache
AI and Ethics (2024)
Closed Access
Explainability of COVID-19 Classification Models Using Dimensionality Reduction of SHAP Values
Daniel Kühn, Melina Silva de Loreto, Mariana Recamonde‐Mendoza, et al.
Lecture notes in computer science (2023), pp. 415-430
Closed Access
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