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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:

Don’t Trust ChatGPT when your Question is not in English: A Study of Multilingual Abilities and Types of LLMs
Xiang Zhang, Senyu Li, Bradley Hauer, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 12

Showing 12 citing articles:

Health information for all: do large language models bridge or widen the digital divide?
Arthur Tang, Neo Tung, Huy Quang Nguyen, et al.
BMJ (2024), pp. e080208-e080208
Closed Access | Times Cited: 6
Explain in Plain Language Questions with Indic Languages: Drawbacks, Affordances, and Opportunities
David H. Smith, Viraj Kumar, Paul Denny
Communications in computer and information science (2025), pp. 3-17
Closed Access
Intelligence artificielle, corpus et diversité linguistique : enjeux et perspectives. Introduction
Rachele Raus, Michela Tonti
Langages (2025) Vol. N° 237, Iss. 1, pp. 7-20
Closed Access
Identifying healthcare needs with patient experience reviews using ChatGPT
Jiaxuan Li, Yunchu Yang, Rong Chen, et al.
PLoS ONE (2025) Vol. 20, Iss. 3, pp. e0313442-e0313442
Open Access
Exploring dual language teachers’ experiences, perceptions and pedagogical implications of ChatGPT in emergent bilingual education
Magdalena Pando, Maricela León, Caitlín A. Dougherty, et al.
Bilingual Research Journal (2025), pp. 1-15
Open Access
Can interactive artificial intelligence be used for patient explanations of nuclear medicine examinations in Japanese?
Norikazu Matsutomo, Mitsuha Fukami, Tomoaki Yamamoto
Annals of Nuclear Medicine (2025)
Closed Access
Playing with words: Comparing the vocabulary and lexical diversity of ChatGPT and humans
Pedro Reviriego Vasallo, Javier Conde, Elena Merino Gómez, et al.
Machine Learning with Applications (2024) Vol. 18, pp. 100602-100602
Open Access | Times Cited: 3
Assessing the Current Limitations of Large-Language Models in Advancing Healthcare Education (Preprint)
JaeYong Kim, Bathri Vajravelu
JMIR Formative Research (2024) Vol. 9, pp. e51319-e51319
Open Access | Times Cited: 2
Evaluation of large language models for the classification of medical device software
Yu Han, Aaron Ceross, Florence T. Bourgeois, et al.
Bio-Design and Manufacturing (2024) Vol. 7, Iss. 5, pp. 819-822
Closed Access | Times Cited: 1
Advancing artificial intelligence in fisheries requires novel cross-sector collaborations
Kate Wing, Benjamin Woodward
ICES Journal of Marine Science (2024) Vol. 81, Iss. 10, pp. 1912-1919
Open Access | Times Cited: 1
Comparative Analysis of the Response Accuracies of Large Language Models in the Korean National Dental Hygienist Examination Across Korean and English Questions
Eun Sun Song, Seung‐Pyo Lee
International Journal of Dental Hygiene (2024)
Open Access | Times Cited: 1
Explorando o Potencial e a Viabilidade de LLMs Open-Source na Análise de Sentimentos
Breno Braga Neves, Theo Sousa, Daniel Coutinho, et al.
(2024), pp. 89-98
Closed Access
Performance of ChatGPT in the In-Training Examination for Anesthesiology and Pain Medicine Residents in South Korea: Observational Study (Preprint)
Soo‐Hyuk Yoon, Seok Kyeong Oh, Byung Gun Lim, et al.
(2024)
Closed Access
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