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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:

Explainable Artificial Intelligence (XAI)
Mitra Tithi Dey
Advances in environmental engineering and green technologies book series (2024), pp. 333-362
Closed Access | Times Cited: 137

Showing 1-25 of 137 citing articles:

A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities
Sergio González, Salvador García, Javier Del Ser, et al.
Information Fusion (2020) Vol. 64, pp. 205-237
Closed Access | Times Cited: 410
Leveraging Data Science to Combat COVID-19: A Comprehensive Review
Siddique Latif, Muhammad Usman, Sanaullah Manzoor, et al.
IEEE Transactions on Artificial Intelligence (2020) Vol. 1, Iss. 1, pp. 85-103
Open Access | Times Cited: 226
Explaining anomalies detected by autoencoders using Shapley Additive Explanations
Liat Antwarg, Ronnie Mindlin Miller, Bracha Shapira, et al.
Expert Systems with Applications (2021) Vol. 186, pp. 115736-115736
Closed Access | Times Cited: 220
Gamut
Fred Hohman, Andrew Head, Rich Caruana, et al.
(2019)
Closed Access | Times Cited: 196
Resilient Chatbots
Zahra Ashktorab, Mohit Jain, Q. Vera Liao, et al.
(2019), pp. 1-12
Closed Access | Times Cited: 169
Explainable Recommendation: A Survey and New Perspectives
Yongfeng Zhang, Xu Chen
(2020)
Open Access | Times Cited: 155
Scenario-based prediction of climate change impacts on building cooling energy consumption with explainable artificial intelligence
Debaditya Chakraborty, Arafat Alam, Saptarshi Chaudhuri, et al.
Applied Energy (2021) Vol. 291, pp. 116807-116807
Closed Access | Times Cited: 118
Transparency and accountability in AI decision support: Explaining and visualizing convolutional neural networks for text information
Buomsoo Kim, Jinsoo Park, Jihae Suh
Decision Support Systems (2020) Vol. 134, pp. 113302-113302
Closed Access | Times Cited: 128
Levels of explainable artificial intelligence for human-aligned conversational explanations
Richard Dazeley, Peter Vamplew, Cameron Foale, et al.
Artificial Intelligence (2021) Vol. 299, pp. 103525-103525
Open Access | Times Cited: 90
Evolving Rule-Based Explainable Artificial Intelligence for Unmanned Aerial Vehicles
Blen Keneni, Devinder Kaur, Ali Al Bataineh, et al.
IEEE Access (2019) Vol. 7, pp. 17001-17016
Open Access | Times Cited: 85
Co-Designing AI Literacy Exhibits for Informal Learning Spaces
Duri Long, Takeria Blunt, Brian Magerko
Proceedings of the ACM on Human-Computer Interaction (2021) Vol. 5, Iss. CSCW2, pp. 1-35
Closed Access | Times Cited: 58
It is Not “Accuracy vs. Explainability”—We Need Both for Trustworthy AI Systems
Dragutin Petković
IEEE Transactions on Technology and Society (2023) Vol. 4, Iss. 1, pp. 46-53
Open Access | Times Cited: 28
Improving IoT Security With Explainable AI: Quantitative Evaluation of Explainability for IoT Botnet Detection
Rajesh Kalakoti, Hayretdin Bahşi, Sven Nõmm
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 10, pp. 18237-18254
Closed Access | Times Cited: 11
Applications, Challenges, and Future Directions of Human-in-the-Loop Learning
Sushant Kumar, Sumit Datta, Vishakha Singh, et al.
IEEE Access (2024) Vol. 12, pp. 75735-75760
Open Access | Times Cited: 11
الدور الوسيط للذكاء الاصطناعي القابل للتفسير في العلاقة بين حوكمة البيانات والأداء المؤسسي
مديح ناير الجداوي
المجلة العربية للعلوم الإدارية. (2024) Vol. 30, Iss. 1, pp. 67-13
Open Access | Times Cited: 11
Interpretable Multiview Early Warning System Adapted to Underrepresented Student Populations
Alberto Cano, John D. Leonard
IEEE Transactions on Learning Technologies (2019) Vol. 12, Iss. 2, pp. 198-211
Closed Access | Times Cited: 72
Ethics of Artificial Intelligence
Sylvester A. Johnson, Michael Ridley, Geneva Henry, et al.
Research Library Issues (2019), Iss. 299
Open Access | Times Cited: 62
Tackling COVID-19 through Responsible AI Innovation: Five Steps in the Right Direction
David Leslie
Harvard data science review (2020)
Open Access | Times Cited: 57
Detecting Troll Behavior via Inverse Reinforcement Learning: A Case Study of Russian Trolls in the 2016 US Election
Luca Luceri, Silvia Giordano, Emilio Ferrara
Proceedings of the International AAAI Conference on Web and Social Media (2020) Vol. 14, pp. 417-427
Open Access | Times Cited: 53
An Empirical Evaluation of AI Deep Explainable Tools
Yoseph Hailemariam, Abbas Yazdinejad, Reza M. Parizi, et al.
2022 IEEE Globecom Workshops (GC Wkshps) (2020), pp. 1-6
Closed Access | Times Cited: 53
Exploring and Promoting Diagnostic Transparency and Explainability in Online Symptom Checkers
Chun-Hua Tsai, Yue You, Xinning Gui, et al.
(2021)
Closed Access | Times Cited: 53
Measuring Explainability and Trustworthiness of Power Quality Disturbances Classifiers Using XAI—Explainable Artificial Intelligence
Ram Machlev, M. Perl, Juri Belikov, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 8, pp. 5127-5137
Closed Access | Times Cited: 42
Sentiment Analysis Meets Explainable Artificial Intelligence: A Survey on Explainable Sentiment Analysis
Arwa Diwali, Kawther Saeedi, Kia Dashtipour, et al.
IEEE Transactions on Affective Computing (2023) Vol. 15, Iss. 3, pp. 837-846
Closed Access | Times Cited: 19
Leveraging complexity frameworks to refine theories of engagement: Advancing self‐regulated learning in the age of artificial intelligence
Jonathan C. Hilpert, Jeffrey A. Greene, Matthew L. Bernacki
British Journal of Educational Technology (2023) Vol. 54, Iss. 5, pp. 1204-1221
Open Access | Times Cited: 17
Assessing Artificial Intelligence for Humanity: Will AI be the Our Biggest Ever Advance ? or the Biggest Threat [Opinion]
Andrzej Nowak, Paul Lukowicz, Paweł Horodecki
IEEE Technology and Society Magazine (2018) Vol. 37, Iss. 4, pp. 26-34
Open Access | Times Cited: 53
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