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ChatGPT: not all languages are equal
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“Additionally, GPT-3.5 exhibits a decline in NLP proficiency in non-English languages relative to English [20].”
From Performance of GPT-3.5 and GPT-4 on the Japanese Medical Licensing Examination: Comparison Study (2023) · cites this paper as [20]
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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots
Gill, S. S., Xu, M., Patros, P., Wu, H., Kaur, R., Kaur, K., Fuller, S., Singh, M., Arora, P., Parlikad, A. K., et al. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.06.002 · Cited by 638
“Despite the technology divide, ChatGPT has seen the greatest consumer growth since its introduction and currently supports more than 100 million active users [4].”
BackgroundGenerative AI in Medicine and Healthcare: Promises, Opportunities and Challenges
Zhang, P., & Kamel Boulos, M. N. (2023) · Future Internet · doi:10.3390/fi15090286 · Cited by 411
“Generative AI is also prone to various forms of bias depending on how it has been trained [41] and may not always perform equally well across different languages [56].”
BackgroundAcademic integrity and artificial intelligence: is ChatGPT hype, hero or heresy?
Currie, G. M. (2023) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2023.04.008 · Cited by 283
Performance of GPT-3.5 and GPT-4 on the Japanese Medical Licensing Examination: Comparison Study
Takagi, S., Watari, T., Erabi, A., & Sakaguchi, K. (2023) · JMIR Medical Education · doi:10.2196/48002 · Cited by 271
ChatGPT in education: Methods, potentials, and limitations
Memarian, B., & Doleck, T. (2023) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2023.100022 · Cited by 266
ChatGPT: Vision and challenges
Gill, S. S., & Kaur, R. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.05.004 · Cited by 294
“ChatGPT is mostly used for data analysis applications, such as gathering data from scientific research papers [6].”
BackgroundMethodInfluentialSohail, S. S., Farhat, F., Himeur, Y., Nadeem, M., Madsen, D. Ø., Singh, Y., Atalla, S., & Mansoor, W. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101675 · Cited by 192
“A few authors also questioned ChatGPT’s efficiency in cyber security (Mijwil et al., 2023) and its potential for biases due to algorithms (Wang, 2023b), region (Wang et al., 2023), and language (Seghier, 2023).”
From Fiction to Fact: The Growing Role of Generative AI in Business and Finance
Chen, B., Wu, Z., & Zhao, R. (2023) · Journal of Chinese Economic and Business Studies · doi:10.1080/14765284.2023.2245279 · Cited by 231
“An example of the current bias in generative AI is that ChatGPT is better at understanding content written in English than text in other languages (Seghier, 2023).”
BackgroundRevolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine
Zhang, K., Meng, X., Yan, X., Ji, J., Liu, J., Xu, H., Zhang, H., Liu, D., Wang, J., Wang, X., et al. (2024) · Journal of Medical Internet Research · doi:10.2196/59069 · Cited by 148
“This broad adoption must span various geographical regions and encompass diverse languages and cultural contexts, catering to users speaking English, Chinese, or local dialects [111,112].”
Nakaura, T., Ito, R., Ueda, D., Nozaki, T., Fushimi, Y., Matsui, Y., Yanagawa, M., Yamada, A., Tsuboyama, T., Fujima, N., et al. (2024) · Japanese Journal of Radiology · doi:10.1007/s11604-024-01552-0 · Cited by 131
“Although the precise performance of LLMs may exhibit variance based on language [46], these facts suggest that LLMs may be able to play a supplementary role even in quite specialized radiology work, even if only for text data at this point.”
BackgroundCadamuro, J., Cabitza, F., Debeljak, Ž., Bruyne, S. D., Frans, G., Pérez, S. M., Özdemir, H., Tolios, A., Carobene, A., & Padoan, A. (2023) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2023-0355 · Cited by 126
“As a major pitfall in using this chatbot, it should be considered that the richness of ChatGPT ’ s response and the intelligibility of its writing in some languages, including French and Arabic, are notably inferior to those in English [32].”
ResultZong, H., Li, J., Wu, E., Wu, R., Lu, J., & Shen, B. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05125-7 · Cited by 114
“Possible explanations for this performance difference include language and cultural differences, variations in examination content [26].”
BackgroundHuang, X., Estau, D., Liu, X., Yu, Y., Qin, J., & Li, Z. (2023) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.15896 · Cited by 123
“32 In particular, it is not open to the public in China, potentially leading to informational gaps regarding Chinese patent medicines.”
BackgroundChatGPT failed Taiwan’s Family Medicine Board Exam
Weng, T.-L., Wang, Y.-M., Chang, S., Chen, T.-J., & Hwang, S.-J. (2023) · Journal of the Chinese Medical Association · doi:10.1097/jcma.0000000000000946 · Cited by 100
Rossettini, G., Rodeghiero, L., Corradi, F., Cook, C., Pillastrini, P., Turolla, A., Castellini, G., Chiappinotto, S., Gianola, S., & Palese, A. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05630-9 · Cited by 103
Jin, H. K., Lee, H. E., & Kim, E. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05944-8 · Cited by 85
Madrid-García, A., Rosales, Z., Freites, D., Pérez-Sancristóbal, I., Pato-Cour, E., Plasencia‐Rodríguez, C., Osorio, L. C., Abásolo, L., León, L., Fernández‐Gutiérrez, B., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-49483-6 · Cited by 81
Improving radiology workflow using ChatGPT and artificial intelligence
Meşe, İ., Taşlıçay, C. A., & Sivrioğlu, A. K. (2023) · Clinical Imaging · doi:10.1016/j.clinimag.2023.109993 · Cited by 61
Watari, T., Takagi, S., Sakaguchi, K., Nishizaki, Y., Shimizu, T., Yamamoto, Y., & Tokuda, Y. (2023) · JMIR Medical Education · doi:10.2196/52202 · Cited by 54
“These limitations may lead to irrelevant or incorrect responses and conclusions [19,26].”
BackgroundWatters, C., & Lemański, M. K. (2023) · Frontiers in Big Data · doi:10.3389/fdata.2023.1224976 · Cited by 64
ChatGPT and Patient Information in Nuclear Medicine: GPT-3.5 Versus GPT-4
Currie, G. M., Robbie, S., & Tually, P. (2023) · Journal of Nuclear Medicine Technology · doi:10.2967/jnmt.123.266151 · Cited by 55
Applications of artificial intelligence and machine learning in clinical medicine: What lies ahead ?
Raj, G. M., Dananjayan, S., & Gudivada, K. K. (2024) · Medicine Advances · doi:10.1002/med4.62 · Cited by 42
Bisi, T., Risser, A., Clavert, P., Migаud, H., & Dаrtus, J. (2023) · Orthopaedics & Traumatology Surgery & Research · doi:10.1016/j.otsr.2023.103694 · Cited by 40
Tong, W., Guan, Y., Chen, J., Huang, X., Zhong, Y., Zhang, C., & Zhang, H. (2023) · Frontiers in Medicine · doi:10.3389/fmed.2023.1237432 · Cited by 39
Liu, Y., Park, Y., & Wang, H. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.104176 · Cited by 50
Artificial scholarship: LLMs in health professions education research
Ellaway, R. H., & Tolsgaard, M. (2023) · Advances in Health Sciences Education · doi:10.1007/s10459-023-10257-4 · Cited by 36
“( Seghier 2023 )”
One hundred important questions facing plant science derived using a large language model
Agathokleous, E., Rillig, M. C., Peñuelas, J., et al. (2023) · Trends in Plant Science · doi:10.1016/j.tplants.2023.06.008 · Cited by 28
Yao, Z., Duan, L., Xu, S., Chi, L., & Sheng, D. (2025) · JMIR Medical Informatics · doi:10.2196/69485 · Cited by 33
“This disparity can be attributed to the preponderance of English-centric data in the training corpora, coupled with a limited inclusion of non-English content, leading to remarkable performance within English linguistic settings but less satisfactory results in non-English environments [10].”
Filetti, S., Fenza, G., & Gallo, A. (2024) · Endocrine · doi:10.1007/s12020-024-03977-z · Cited by 37
“Most LLMs are trained on extensive English datasets, leading to challenges for other languages: – Competitive disadvantage : English-centric LLMs may struggle with the nuances of other languages, leading to inaccurate translations and misinterpretations [50].”
ChatGPT in Medical Education: Bibliometric and Visual Analysis
Zhang, Y., Xie, X., & Xu, Q. (2025) · JMIR Medical Education · doi:10.2196/72356 · Cited by 35
Ming, S., Guo, Q., Cheng, W., & Lei, B. (2024) · JMIR Medical Education · doi:10.2196/52784 · Cited by 25
“While ChatGPT’s accuracy varies across languages [3], it has been tested on a series of medical exams like the Japanese National Medical Licensing Examination in languages including English [4], Chinese [5], Dutch [6], Japanese [7], and Korean [8].”
BackgroundLiu, C., & Chou, J. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105891 · Cited by 24
Adilmetova, G., Nassyrov, R., Meyerbekova, A., Karabay, A., Varol, H. A., & Chan, M. (2024) · Journal of Nutrition · doi:10.1016/j.tjnut.2024.12.018 · Cited by 29
Ozkan, E., Tekin, A., Ozkan, M. C., Cabrera, D., Niven, A. S., & Dong, Y. (2025) · JMIR Medical Education · doi:10.2196/58801 · Cited by 23
Nakajima, N., Fujimori, T., Furuya, M., Kanie, Y., Imai, H., Kita, K., Uemura, K., & Okada, S. (2024) · Cureus · doi:10.7759/cureus.56402 · Cited by 21
“5 was its lower accuracy in non-English languages [22], which was particularly evident in the Japanese medical licensing exam where GPT-3.”
BackgroundExploring the Current Applications and Effectiveness of ChatGPT in Nursing: An Integrative Review
Luo, Y., Miao, Y., Zhao, Y., Li, J., & Wu, Y. X. (2024) · Journal of Advanced Nursing · doi:10.1111/jan.16628 · Cited by 22
ChatGPT as an effective tool for quality evaluation of radiomics research
Meşe, İ., & Koçak, B. (2024) · European Radiology · doi:10.1007/s00330-024-11122-7 · Cited by 19
Lee, G. U., Hong, D. Y., Kim, S. Y., Kim, J. W., Lee, Y. H., Park, S. O., & Lee, K. R. (2024) · Medicine · doi:10.1097/md.0000000000037325 · Cited by 17
“[15] For example, ChatGPT-3.”
The impact of ChatGPT on human data collection: A case study involving typicality norming data
Heyman, T., & Heyman, G. (2023) · Behavior Research Methods · doi:10.3758/s13428-023-02235-w · Cited by 20
“On the flip side, the quality of the English output tends to be superior compared to other languages (Seghier, 2023), which could improve the correlation.”
BackgroundChatGPT: oportunidades y riesgos en la asistencia, docencia e investigación médica
Gutiérrez‐Cirlos, C., Carrillo‐Pérez, D. L., Bermudez‐Gonzalez, J. L., Hidrogo-Montemayor, I., Carrillo-Esper, R., & Mendiola, M. S. (2023) · Gaceta Médica de México · doi:10.24875/gmm.230001671 · Cited by 39
A retrospective evaluation of the potential of ChatGPT in the accurate diagnosis of acute stroke
Kuzan, B. N., Meşe, İ., Yaşar, S., et al. (2024) · Diagnostic and Interventional Radiology · doi:10.4274/dir.2024.242892 · Cited by 16
Accuracy of large language models in answering ophthalmology board-style questions: A meta-analysis
Wu, J.-H., Nishida, T., & Liu, T. Y. A. (2024) · Asia-Pacific Journal of Ophthalmology · doi:10.1016/j.apjo.2024.100106 · Cited by 16
Using ChatGPT and other AI ‐assisted tools to improve manuscripts readability and language
Seghier, M. L. (2023) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22902 · Cited by 15
Self-citationRos‐Arlanzón, P., & Sempere, Á. P. (2024) · JMIR Medical Education · doi:10.2196/56762 · Cited by 14
“Unlike most existing literature that evaluates AI in English [28], our study probes ChatGPT’s performance in Spanish, a vital consideration for global medical applications given the variation in medical terminology and nuances across languages.”
Lukešová, A., & Jennings, P. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2025.2612532 · Cited by 16
Cognitive decline assessment in speakers of understudied languages
Hatahet, O., Röser, F., & Seghier, M. L. (2023) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12432 · Cited by 13
“There is, for instance, an interest in the development of AI-based cognitive tests, 95 including chatbots powered by the like of ChatGPT to conduct cognitive tests, butthesechatbotsbasedonlargelanguagemodelsdonotperformwell in all languages (e.g., Seghier 96 ).”
MethodSelf-citationPerformance of GPT-3.5 and GPT-4 on the Korean Pharmacist Licensing Examination: Comparison Study
Jin, H. K., & Kim, E. Y. (2024) · JMIR Medical Education · doi:10.2196/57451 · Cited by 11
“Moreover, disparity in performance might be attributed to differences in language and culture, as well as variations in the content of the examinations [32].”
Beyond borders or building new walls?
Tran, H., & Stell, A. (2024) · Australian Review of Applied Linguistics · doi:10.1075/aral.24135.tra · Cited by 13
Using A Google Web Search Analysis to Assess the Utility of ChatGPT in Stem Cell Therapy
Chen, L., Li, H., Su, Y., Yang, Z., He, Z., Wang, D., Li, J. J., & Xing, D. (2023) · Stem Cells Translational Medicine · doi:10.1093/stcltm/szad074 · Cited by 11
“26 The accuracy of information provided by ChatGPT is crucial for clinicians and patients in decision-making and for patients in prediagnosis education, including in the area of stem cell therapy.”
BackgroundBarrot, J. S. (2024) · Springer eBooks · doi:10.1007/978-3-031-67667-3_13 · Cited by 10
Guo, K., Zhan, C., & Li, X. (2025) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-025-02772-x · Cited by 11
The ChatGPT revolution: Reshaping education through artificial intelligence
Kaur, K., Shilpa, & Jindal, R. (2024) · AIP Conference Proceedings · doi:10.1063/5.0221430 · Cited by 7
New possibilities of artificial intelligence in medicine: a narrative review
Litvin, A., Стома, И. О., Михайловна, Ш. Т., Rumovskaya, S. B., & Kyovalev, A. A. (2024) · Health and Ecology Issues · doi:10.51523/2708-6011.2024-21-1-01 · Cited by 9
Luo, Y., Miao, Y., Zhao, Y., Li, J., Chen, Y., Yue, Y., & Wu, Y. X. (2024) · JMIR Formative Research · doi:10.2196/63188 · Cited by 9
“Previous studies have found that ChatGPT could provide relatively precise health information in the English context [13,14].”
Li, Z., Yan, C., Cao, Y., Gong, A., Li, F., & Zeng, R. (2025) · Scientific Reports · doi:10.1038/s41598-025-04309-5 · Cited by 8
“Recent studies have highlighted the importance of investigating cross-linguistic variations in LLM performance 7,38 .”
Kottlors, J., Iuga, A.-I., Blüthgen, C., Bressem, K. K., Kather, J. N., Moy, L. P., Wald, C., Wang, W., Liu, T., Ranschaert, E. R., et al. (2026) · Radiology · doi:10.1148/radiol.250913 · Cited by 13
Yıldız, M. S., & Alper, A. (2023) · Journal of Consumer Health on the Internet · doi:10.1080/15398285.2023.2240652 · Cited by 9
Liu, X., & Zhang, Z.-R. (2024) · World Journal of Psychiatry · doi:10.5498/wjp.v14.i3.334 · Cited by 8
Lee, J. K., Choi, S., Park, S., Hwang, S., & Cho, D. (2025) · Annals of Laboratory Medicine · doi:10.3343/alm.2024.0588 · Cited by 7
“This finding contrasts with those of Seghier, who re-ported that performance varied depending on the language used [21].”
Lian, L., Luo, X., Chipusu, K., Ashraf, M. A., Wong, K. K. L., & Zhang, W. (2026) · Bioengineering · doi:10.3390/bioengineering13010113 · Cited by 18
“Additionally, while ChatGPT shows a decline in non-English language capabilities compared to English [15], in this study, GPT-4o scored comparably to Ernie Bot 4.0 across all aspects, particularly excelling in Basic Medical knowledge—a universally applicable medical field—with an accuracy of…”
InfluentialDu, D., Yang, P., Zhao, L., An, W., Wang, Z., & Yu, S. (2023) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.3c01097 · Cited by 6
ChatGPT-A Generative Pre-Trained Transformer
Gupta, M. R. (2024) · International Journal of Advanced Research in Science Communication and Technology · doi:10.48175/ijarsct-15087 · Cited by 6
Dermatology “AI Babylon”: Cross-Language Evaluation of AI-Crafted Dermatology Descriptions
Karampinis, E., Zoumpourli, C.-M., Kontogianni, C., Arkoumanis, P. T., Koumaki, D., Mantzaris, D. H., Filippakis, K., Papadopoulou, M.-M., Theofili, M., Enechukwu, N. A., et al. (2026) · Medicina · doi:10.3390/medicina62010227 · Cited by 5
“[31] French and Arabic Testing of ChatGPT in a set of neuroscience questions.”
Torales, J. C., & O’Higgins, M. G. (2023) · International Journal of Social Psychiatry · doi:10.1177/00207640231178488 · Cited by 5
Beyond the interface: Supporting beginner-level CEFR mediation and learner autonomy with ChatGPT
Lukešová, A., & Jennings, P. J. (2025) · Language Teaching Research · doi:10.1177/13621688251393481 · Cited by 4
The Game-Changing Impact of AI Chatbots on Education ChatGPT and Beyond
Vasudevan, A., Lama, A. V., & Sain, Z. H. (2024) · Journal of Information Systems and Technology Research · doi:10.55537/jistr.v3i1.770 · Cited by 4
Suitability of ChatGPT as a Source of Patient Information for Screening Mammography
Spuur, K. M., Currie, G. M., Al‐Mousa, D. S., & Pape, R. (2024) · Health Promotion Practice · doi:10.1177/15248399241285060 · Cited by 5
“ChatGPT might be better suited to language conversion of exemplar clinical patient information sheets where English is a second language, although ChatGPT has been reported to be inferior in non-English language text generation (Seghier, 2023).”
Perspectives on the use of ChatGPT in academic publications
Kardeş, G., & Oran, N. T. (2024) · Science and Public Policy · doi:10.1093/scipol/scae079 · Cited by 4
Conducting sociolinguistic interviews via generative AI: A methods tutorial
Stell, A., Tran, H., & Crosthwaite, P. R. (2025) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2025.100223 · Cited by 3
Xiao, J., Li, M., Cai, R., Huang, H., Yu, H., Huang, L., Li, J. W., Yu, T., Zhang, J., & Cheng, S. (2025) · Journal of Medical Internet Research · doi:10.2196/56737 · Cited by 3
“The lack of culturally specific knowledge and the latest medical literature and data in other languages is a significant limitation of ChatGPT, which may lead to irrelevant or incorrect answers and conclusions [33,34].”
LLMs for Question-Answer and Synthetic Data Generation and Evaluation
Balyan, R., Thompson, K., & Iacobelli, F. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98284-2_2 · Cited by 3
Evaluating the performance of ChatGPT in clinical pharmacyPreprint
Huang, X., Estau, D., Liu, X., Yu, Y., Qin, J., & Li, Z. (2023) · doi:10.22541/au.168253193.31991662/v1 · Cited by 3
Incorporating ChatGPT Into Online Discussions in a Literacy Course
Hu, R., & Lin, X. Y. (2025) · International Journal of Artificial Intelligence · doi:10.4018/ijaitl.366589 · Cited by 2
Rostkowski, E., Rushton, N., Smith, H., & Shaw, S. T. (2025) · Scatterplot · doi:10.1080/29932955.2025.2572149 · Cited by 2
Qi, B., Zheng, Y., Wang, Y., & Xu, L. (2025) · JMIR Formative Research · doi:10.2196/79534 · Cited by 4
“Previous studies have shown that language effects are particularly evident in tasks requiring specific cultural background knowledge or relying on the latest literature and data in other languages [28], which may further account for the differences in model performance.”
Bisi, T., Risser, A., Clavert, P., Migаud, H., & Dаrtus, J. (2023) · Revue de Chirurgie Orthopédique et Traumatologique · doi:10.1016/j.rcot.2023.09.014 · Cited by 5
Kerbage, A., Burke, C. A., & Rouphael, C. (2024) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2024.03.040 · Cited by 2
Филимонова, И. В. (2023) · Человеческий капитал. · doi:10.25629/hc.2023.12.54 · Cited by 2
Laskowski, M., Ciekalski, M., Laskowski, M., Błaszczyk, B., Marcin, S., Paździora, P., & Rudnik, A. (2024) · Annales Academiae Medicae Silesiensis · doi:10.18794/aams/186827 · Cited by 3
“5 shows reduced proficiency in non-English languages compared to its performance in English [10].”
BackgroundTeachers’ opinions on the application of corpora in ICT and AI-aided foreign language education
Polok, K., Drózd, A., & Przybysz-Zaremba, M. (2025) · The Journal of Educational Research · doi:10.1080/00220671.2025.2510381 · Cited by 2
“Due to the fact that it is a machine, not a living being, it seems necessary to attentively and very precisely inform the chatbot what it is expected to produce, but even then some (luckily, not too many) errors are possible (Seghier, 2023).”
Zhou, Z., Ji, X., Zhang, J., Zhao, Z., Hei, X., & Choo, K. R. (2025) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-93354-7_15 · Cited by 3
Cross-lingual effects of AI-generated content on human work
Koo, W. W.-Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-16650-w · Cited by 8
Chimbunde, P., & Moreeng, B. B. (2025) · TechTrends · doi:10.1007/s11528-025-01062-4 · Cited by 3
“Seghier (2023) writes limiting or forbidding ChatGPT will not solve the problem, rather it is preferable to accept it and establish explicit guidelines for its application in academic settings which is supported by the disruptive technology theory which argues for the adoption of new technologies.”
Balzotti, A., Gallelli, R., Renna, P., Ascione, A., Amati, I., Casolaro, M., & Depalo, L. (2025) · Studies in computational intelligence · doi:10.1007/978-3-031-82915-4_6 · Cited by 1
The Future of Artificial Intelligence and Artificial Intelligence in Primary Care
Cheema, A. M. (2025) · Primary Care Clinics in Office Practice · doi:10.1016/j.pop.2025.07.011 · Cited by 1
Ignjatović, A., Apostolovic, M. A., Stevanović, L., Radovanović, P., Sidharth, Topalović, M., & Filipović, T. (2025) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205251409530 · Cited by 1
A systematic review of ChatGPT in education and scientific research: Insights from a SWOT analysis
Abdullahi, A., Ahmed, M. Y., & Hussein, H. A. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.102720 · Cited by 2
Asking ChatGPT for Pattern Recommendations: EuroPLoP 2024 Focus Group Report
Laue, R., Maranhão, J. J., & Guerra, E. (2024) · European Conference on Pattern Languages of Programs · doi:10.1145/3698322.3698361 · Cited by 1
Ming, S., Guo, Q., Cheng, W., & Lei, B. (2023) · doi:10.2196/preprints.52784 · Cited by 2
AI-based ChatGPT Impact on Medical Writing and Publication
Mofan, L., Zhang, M. Y., Sun, M. Y., Cui, P. L., & Wang, P. S. (2023) · Advanced ultrasound in diagnosis and therapy · doi:10.37015/audt.2023.230013
Adilmetova, G., Nassyrov, R., Meyerbekova, A., Karabay, A., Varol, H. A., & Chan, M. (2024) · doi:10.2196/preprints.56322
Ros‐Arlanzón, P., & Sempere, Á. P. (2024) · doi:10.2196/preprints.56762
Global Healthcare Professionals’ Perceptions of Large Language Model Use In Practice (Preprint)Preprint
Ozkan, E., Tekin, A., Ozkan, M. C., Cabrera, D., Niven, A. S., & Dong, Y. (2024) · doi:10.2196/preprints.58801
ChatGPT and Unified State Exam in Computer Science
Popov, V. S. (2024) · International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE) · doi:10.1109/reepe60449.2024.10479881 · Cited by 1
“The USE tasks in Computer Science were offered in Russian without translation into English, which could also affect the result of the study [23].”
MethodCurrent Use of Generative Artificial Intelligence in Pharmacy Practice: A Literature Mini-review
Kiyomiya, K., Aomori, T., Kawazoe, H., & Ohtani, H. (2025) · Iryo Yakugaku (Japanese Journal of Pharmaceutical Health Care and Sciences) · doi:10.5649/jjphcs.51.177 · Cited by 1
Asthana, A. K. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-3902-3.ch004
Performance of reasoning large language models on nephrology multiple-choice questionsPreprint
Kitano, F., Masaki, M., Ichikawa, D., Shibagaki, Y., & Noda, R. (2025) · medRxiv · doi:10.64898/2025.12.03.25341427
Rossettini, G., Rodeghiero, L., Corradi, F., Cook, C., Pillastrini, P., Turolla, A., Castellini, G., Chiappinotto, S., Gianola, S., & Palese, A. (2024) · Figshare · doi:10.6084/m9.figshare.26739498
Rossettini, G., Rodeghiero, L., Corradi, F., Cook, C., Pillastrini, P., Turolla, A., Castellini, G., Chiappinotto, S., Gianola, S., & Palese, A. (2024) · Figshare · doi:10.6084/m9.figshare.26739489
Rossettini, G., Rodeghiero, L., Corradi, F., Cook, C., Pillastrini, P., Turolla, A., Castellini, G., Chiappinotto, S., Gianola, S., & Palese, A. (2024) · Figshare · doi:10.6084/m9.figshare.26739492
Metadata
- Authors
- Seghier, M. L.
- Affiliations
- Khalifa University of Science and Technology (AE)
- Corresponding author
- Seghier, Mohamed L.
- ORCID
- Seghier, Mohamed L.
- Venue
- Nature
- Published
- 2023-03-07
- Volume
- 615
- Issue
- 7951
- Pages
- 216-216
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W4323360926
- Cited by
- 108
- References
- 0
- Citations by year
- 2026: 9 · 2025: 23 · 2024: 41 · 2023: 34
- FWCI
- 10.09
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- ChatGPT, large language models, language bias, multilingual language models, language inequality
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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