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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 Accuracy: The Role of Mental Models in Human-AI Team Performance
Gagan Bansal, Besmira Nushi, Ece Kamar, et al.
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (2019) Vol. 7, pp. 2-11
Open Access | Times Cited: 314

Showing 1-25 of 314 citing articles:

Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Sajid Ali, Tamer Abuhmed, Shaker El–Sappagh, et al.
Information Fusion (2023) Vol. 99, pp. 101805-101805
Open Access | Times Cited: 608
“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI
Nithya Sambasivan, Shivani Kapania, Hannah Highfill, et al.
(2021), pp. 1-15
Closed Access | Times Cited: 451
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
Sina Mohseni, Niloofar Zarei, Eric D. Ragan
ACM Transactions on Interactive Intelligent Systems (2021) Vol. 11, Iss. 3-4, pp. 1-45
Open Access | Times Cited: 412
Evaluating the Quality of Machine Learning Explanations: A Survey on Methods and Metrics
Jianlong Zhou, Amir H. Gandomi, Fang Chen, et al.
Electronics (2021) Vol. 10, Iss. 5, pp. 593-593
Open Access | Times Cited: 405
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Gagan Bansal, Tongshuang Wu, Joyce Zhou, et al.
(2021), pp. 1-16
Open Access | Times Cited: 363
To Trust or to Think
Zana Buçinca, Maja Barbara Malaya, Krzysztof Z. Gajos
Proceedings of the ACM on Human-Computer Interaction (2021) Vol. 5, Iss. CSCW1, pp. 1-21
Open Access | Times Cited: 294
Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems
Zana Buçinca, Phoebe Lin, Krzysztof Z. Gajos, et al.
(2020)
Open Access | Times Cited: 211
Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making
Xinru Wang, Ming Yin
(2021), pp. 318-328
Open Access | Times Cited: 179
Transitioning to Human Interaction with AI Systems: New Challenges and Opportunities for HCI Professionals to Enable Human-Centered AI
Wei Xu, Marvin J. Dainoff, Liezhong Ge, et al.
International Journal of Human-Computer Interaction (2022) Vol. 39, Iss. 3, pp. 494-518
Open Access | Times Cited: 147
Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI
Andreas Fügener, Jörn Grahl, Alok Gupta, et al.
MIS Quarterly (2021) Vol. 45, Iss. 3, pp. 1527-1556
Open Access | Times Cited: 136
Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice
Leah Chong, Guanglu Zhang, Kosa Goucher-Lambert, et al.
Computers in Human Behavior (2021) Vol. 127, pp. 107018-107018
Open Access | Times Cited: 133
Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review
Haomin Chen, Catalina Gómez, Chien‐Ming Huang, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 122
Recent Advances in Trustworthy Explainable Artificial Intelligence: Status, Challenges, and Perspectives
Atul Rawal, James McCoy, Danda B. Rawat, et al.
IEEE Transactions on Artificial Intelligence (2021) Vol. 3, Iss. 6, pp. 852-866
Open Access | Times Cited: 121
Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey
Weiping Ding, Mohamed Abdel‐Basset, Hossam Hawash, et al.
Information Sciences (2022) Vol. 615, pp. 238-292
Closed Access | Times Cited: 107
Explanations Can Reduce Overreliance on AI Systems During Decision-Making
Helena Vasconcelos, Matthew Jörke, Madeleine Grunde-McLaughlin, et al.
Proceedings of the ACM on Human-Computer Interaction (2023) Vol. 7, Iss. CSCW1, pp. 1-38
Open Access | Times Cited: 99
Where to Hide a Stolen Elephant: Leaps in Creative Writing with Multimodal Machine Intelligence
Nikhil Singh, Guillermo Bernal, Daria Savchenko, et al.
ACM Transactions on Computer-Human Interaction (2022) Vol. 30, Iss. 5, pp. 1-57
Open Access | Times Cited: 73
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, et al.
Proceedings of the ACM on Human-Computer Interaction (2023) Vol. 7, Iss. CSCW2, pp. 1-32
Open Access | Times Cited: 53
Towards a Science of Human-AI Decision Making: An Overview of Design Space in Empirical Human-Subject Studies
Vivian Lai, Chacha Chen, Alison Smith, et al.
2022 ACM Conference on Fairness, Accountability, and Transparency (2023), pp. 1369-1385
Open Access | Times Cited: 51
Rams, hounds and white boxes: Investigating human–AI collaboration protocols in medical diagnosis
Federico Cabitza, Andrea Campagner, Luca Ronzio, et al.
Artificial Intelligence in Medicine (2023) Vol. 138, pp. 102506-102506
Open Access | Times Cited: 48
Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making
Xiaojuan Ma, Ying Lei, Xinru Wang, et al.
(2023), pp. 1-19
Open Access | Times Cited: 47
Social Dynamics of AI Support in Creative Writing
Katy Ilonka Gero, Tao Long, Lydia B. Chilton
(2023), pp. 1-15
Closed Access | Times Cited: 47
Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Making
Kori Inkpen, Shreya Chappidi, Keri Mallari, et al.
ACM Transactions on Computer-Human Interaction (2023) Vol. 30, Iss. 5, pp. 1-29
Open Access | Times Cited: 45
Exploring Challenges and Opportunities to Support Designers in Learning to Co-create with AI-based Manufacturing Design Tools
Frederic Gmeiner, Humphrey Yang, Lining Yao, et al.
(2023), pp. 1-20
Open Access | Times Cited: 42
Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale
Jae Hyuk Kim, Sun Kyung Kim, Jongmyung Choi, et al.
Digital Health (2024) Vol. 10
Open Access | Times Cited: 26
Larger and more instructable language models become less reliable
Lexin Zhou, Wout Schellaert, Fernando Martínez‐Plumed, et al.
Nature (2024) Vol. 634, Iss. 8032, pp. 61-68
Open Access | Times Cited: 26
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