The DOI matches its Crossref record.
ChatGPT: not all languages are equal
Overview
Integrity signals
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Cites
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Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Citations
Cited by
Sorted by citations
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
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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