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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:

Beyond generalization: a theory of robustness in machine learning
Timo Freiesleben, Thomas Grote
Synthese (2023) Vol. 202, Iss. 4
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Trust, Explainability and AI
Sam Baron
Philosophy & Technology (2025) Vol. 38, Iss. 1
Open Access | Times Cited: 3
Machine learning robustness: a primer
Houssem Ben Braiek, Foutse Khomh
Elsevier eBooks (2025), pp. 37-71
Open Access | Times Cited: 3
The Role of Humanization and Robustness of Large Language Models in Conversational Artificial Intelligence for Individuals With Depression: A Critical Analysis
Andrea Ferrario, Jana Sedláková, Manuel Trachsel
JMIR Mental Health (2024) Vol. 11, pp. e56569-e56569
Open Access | Times Cited: 9
A scoping review of robustness concepts for machine learning in healthcare
Alan Balendran, Céline Béji, Florie Bouvier, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access | Times Cited: 1
Reliability in Machine Learning
Thomas Grote, Konstantin Genin, Emily Sullivan
Philosophy Compass (2024) Vol. 19, Iss. 5
Open Access | Times Cited: 6
Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: beyond algorithm development
Mohd Nur Ikhmal Salehmin, Tiong Sieh Kiong, Hassan Mohamed, et al.
Journal of Energy Chemistry (2024) Vol. 99, pp. 223-252
Closed Access | Times Cited: 6
The fundamentals of AI ethics in medical imaging
Julia Amann, Valerie Burger, Michelle Livne, et al.
Elsevier eBooks (2025), pp. 7-33
Closed Access
Real-time Model-based Condition Monitoring of Geothermal Systems under Uncertainties – Case Study on Electrical Submersible Pumps
Pejman Shoeibi Omrani, Y.T. Yang, H.H.M. Rijnaarts, et al.
Geoenergy Science and Engineering (2025), pp. 213775-213775
Open Access
From human-centered to symbiotic artificial intelligence: a focus on medical applications
Giuseppe Desolda, Andrea Esposito, Rosa Lanzilotti, et al.
Multimedia Tools and Applications (2024)
Open Access | Times Cited: 4
Transparency Distortion Robustness for SOTA Image Segmentation Tasks
Volker Knauthe, Arne Rak, Tristan Wirth, et al.
Lecture notes in computer science (2025), pp. 3-16
Closed Access
Fortifying Trust: Can Computational Reliabilism Overcome Adversarial Attacks?
Paweł Pawłowski, Kristian González Barman
Philosophy & Technology (2025) Vol. 38, Iss. 1
Closed Access
Robustness of Machine Learning Predictions for Determining Whether Deep Inspiration Breath-Hold Is Required in Breast Cancer Radiation Therapy
Wlla E. Al-Hammad, Masahiro Kuroda, Ghaida Al Jamal, et al.
Diagnostics (2025) Vol. 15, Iss. 6, pp. 668-668
Open Access
Predicting indoor PM levels in shared office using LSTM method
Junzhou He, Saichong Zhang, Yu Miao, et al.
Journal of Building Engineering (2025), pp. 112407-112407
Closed Access
Reinforcement Learning from Human Feedback in LLMs: Whose Culture, Whose Values, Whose Perspectives?
Kristian González Barman, Simon Lohse, Henk W. de Regt
Philosophy & Technology (2025) Vol. 38, Iss. 2
Open Access
Strategies to Improve the Robustness and Generalizability of Deep Learning Segmentation and Classification in Neuroimaging
Tran Anh Tuan, Tal Zeevi, Seyedmehdi Payabvash
BioMedInformatics (2025) Vol. 5, Iss. 2, pp. 20-20
Open Access
Efficient merging and validation of deep learning-based nuclei segmentations in H&E slides from multiple models
Jagadheshwar Balan, Shannon K. McDonnell, Zachary C. Fogarty, et al.
Journal of Pathology Informatics (2025), pp. 100443-100443
Open Access
AI safety for everyone
Bálint Gyevnár, Atoosa Kasirzadeh
Nature Machine Intelligence (2025)
Closed Access
Percentages and reasons: AI explainability and ultimate human responsibility within the medical field
Markus Herrmann, Andreas Wabro, Eva C. Winkler
Ethics and Information Technology (2024) Vol. 26, Iss. 2
Open Access | Times Cited: 3
Navigating the uncommon: challenges in applying evidence-based medicine to rare diseases and the prospects of artificial intelligence solutions
Olivia Rennie
Medicine Health Care and Philosophy (2024) Vol. 27, Iss. 3, pp. 269-284
Closed Access | Times Cited: 3
Machine learning in healthcare and the methodological priority of epistemology over ethics
Thomas Grote
Inquiry (2024), pp. 1-30
Closed Access | Times Cited: 2
Evaluating the robustness of multimodal task load estimation models
Andreas Foltyn, Jessica Deuschel, Nadine R. Lang-Richter, et al.
Frontiers in Computer Science (2024) Vol. 6
Open Access | Times Cited: 2
Analysis of LLMs for Educational Question Classification and Generation
Said Al Faraby, Ade Romadhony, Adiwijaya Adiwijaya
Computers and Education Artificial Intelligence (2024), pp. 100298-100298
Open Access | Times Cited: 2
Interpretable AI/ML for High-stakes Tasks with Human-in-the-loop: Critical Review and Future Trends
Boris Kovalerchuk
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Making more with Less: Improving Software Testing Outcomes Using a Cross-Project and Cross-Language ML Classifier Based on Cost-Sensitive Training
Alexandre Nascimento, Gabriel Kenji Godoy Shimanuki, Luiz Alberto Vieira Dias
(2024)
Open Access | Times Cited: 1
Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena
Timo Freiesleben, Gunnar König, Christoph Molnar, et al.
Minds and Machines (2024) Vol. 34, Iss. 3
Open Access | Times Cited: 1
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