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the claim

AI text detectors reliably detect AI-generated text that has been paraphrased.

the verdict
INSUFFICIENT LEANING
Recorded sources
0 sources for · 9 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that AI text detectors reliably detect AI-generated text that has been paraphrased?

Unclear. The retrieved sources consistently report that AI text detectors are unreliable and struggle with modified or humanized AI-generated text, but none directly tests detection of paraphrased AI text, so the claim is only partially addressed.

Verdict: PARTIAL LEAN · 0 sources for, 9 against · Last checked

The private library was unavailable for some searches in this check. Missing library results are not evidence against the claim.

Evidence against · 9
AI-generated Text Boundary Detection with RoFT
2024
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AI-generated Text Boundary Detection with RoFT. (2024). hal.science. https://hal.science/hal-04734023v1

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More against · 8
Testing of Detection Tools for AI-Generated Text
2023
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Weber-Wulff, D., Anohina-Naumeca, A., Bjelobaba, S., Foltýnek, T., Guerrero-Dib, J., & Popoola, O. (2023). Testing of Detection Tools for AI-Generated Text. eric.ed.gov. https://doi.org/10.1007/s40979-023-00146-z

Robust AI-Generated Text Detection by Restricted Embeddings
2025
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Robust AI-Generated Text Detection by Restricted Embeddings. (2025). hal.science. https://doi.org/10.18653/v1/2024.findings-emnlp.992

The Effectiveness of Software Designed to Detect AI-Generated Writing: A Comparison of 16 AI Text Detectors
2023
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Walters, W. H. (2023). The Effectiveness of Software Designed to Detect AI-Generated Writing: A Comparison of 16 AI Text Detectors. doi.org. https://doi.org/10.1515/opis-2022-0158

GradEscape: A Gradient-Based Evader Against AI-Generated Text Detectors
2025
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Wenlong, M., Shuguo, F., & Chengkun, W. (2025). GradEscape: A Gradient-Based Evader Against AI-Generated Text Detectors. zenodo.org. https://doi.org/10.5281/zenodo.15807727

Investigating generative AI models and detection techniques: impacts of tokenization and dataset size on identification of AI-generated text.
2024
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Hua, H. & Yao, C. (2024). Investigating generative AI models and detection techniques: impacts of tokenization and dataset size on identification of AI-generated text.. doi.org. https://doi.org/10.3389/frai.2024.1469197

Rethinking Assessment for Engineering Students in Higher Education in the Age of Generative AI: A Critical Narrative Review
2026
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Rethinking Assessment for Engineering Students in Higher Education in the Age of Generative AI: A Critical Narrative Review. (2026). hal.science. https://hal.science/hal-05747639v1

Generative AI and health misinformation: production, propagation, and mitigation-a systematic review.
2026
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HR, S., S, J., N, G., & H, K. (2026). Generative AI and health misinformation: production, propagation, and mitigation-a systematic review.. doi.org. https://doi.org/10.1186/s12889-025-26148-9

AI-Generated Song Detection via Lyrics Transcripts
2025
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Frohmann, M., Epure, E., & Brocal, G. M. (2025). AI-Generated Song Detection via Lyrics Transcripts. zenodo.org. https://doi.org/10.5281/zenodo.17811328

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