Artificial Writing and Automated Detection
Open accessIntegrity signals
Registry
Cites
Statistics
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?
Little is known about how the rise of LLMs is reshaping the public funding landscape.
“Despite growing attention to the use of AI in science (15–27), little is known about how the rise of large language models (LLMs) is reshaping the public funding landscape.”
From The rise of large language models and the direction and impact of US federal research funding (2026) · cites this paper as [24]
Cites
Testing of detection tools for AI-generated text
Weber-Wulff, D., Anohina-Naumeca, A., Bjelobaba, S., Foltýnek, T., Guerrero-Dib, J., Popoola, O., Šigut, P., & Waddington, L. (2023) · International Journal for Educational Integrity · doi:10.1007/s40979-023-00146-z · Cited by 582 · see citing works
Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
Crothers, E. N., Japkowicz, N., & Viktor, H. L. (2023) · IEEE Access · doi:10.1109/access.2023.3294090 · Cited by 196 · see citing works
The Science of Detecting LLM-Generated Text
Tang, R., Chuang, Y.-N., & Hu, X. (2024) · Communications of the ACM · doi:10.1145/3624725 · Cited by 125 · see citing works
The Rapid Adoption of Generative AIPreprint
Blandin, A., Bick, A., & Deming, D. J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4965142 · Cited by 48 · see citing works
Hanley, H. W. A., & Durumeric, Z. (2024) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v18i1.31333 · Cited by 36 · see citing works
Detecting inorganic financial campaigns on Twitter
Tardelli, S., Avvenuti, M., Tesconi, M., & Cresci, S. (2021) · Information Systems · doi:10.1016/j.is.2021.101769 · Cited by 31 · see citing works
Russell, J., Karpinska, M., & Iyyer, M. (2025) · Annual Meeting of the Association for Computational Linguistics (ACL) · doi:10.18653/v1/2025.acl-long.267 · Cited by 19 · see citing works
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The rise of large language models and the direction and impact of US federal research funding
Qian, Y., Wen, Z., Furnas, A. C., Bai, Y., Shao, E., & Wang, D. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2601439123 · Cited by 5 · see citing works
Chakrabarty, T., & Dhillon, P. S. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791276 · Cited by 1 · see citing works
Bryant, A. (2026) · Informatics · doi:10.3390/informatics13070113
- Authors
- Jabarian, B., & Imas, A.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Jabarian, Brian
- ORCID
- Imas, Alex
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2025
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W4414050479
- Cited by
- 3
- References
- 7
- Citations by year
- 2026: 3
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- SSRN Electronic Journal (acceptedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Authorship Attribution and Profiling
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Keywords
- AI-generated text detection, false negative rate, false positive rate, GPTZero, RoBERTa, error tolerance, academic integrity, student assignments, product reviews
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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