I scored the full text of 12,750 arXiv papers from 2021 through 2026 to find out how many of these get flagged as machine written and how much it increased since the release of chatGPT. I purposely tuned the detector to avoid false positives. My detection rate pre chatGPT is around .4% for that reason.

The biggest results: in Jan of 2026 about 39% of papers got flagged as AI written. In computer science speicifcally the peak was at 65%. Mathematics barely moved away from 0.7%, though the proof heavy math texts might just not get picked up by the detector properly.

All this is a detector estimate of a statistical signal and not a proof any given author used AI. Machine written can also mean heavy AI-assisted editing.

Couple of methodological notes

* pre-chatGPT is not an effective control because language evolves. In the arxiv corpus in particular there are "fashions" in research depending on what gets funded lately, not to mention many new words and topics not invented before a given paper.

* In general, detecting AI from content seems difficult as humans write like they read. To the extent there are unique factors recognizable as AI and to the extent humans read them, they will eventually incorporate them into their writing style. Accordingly, you'd need to model a rolling window of "AI tells" that decay at some rate.

This is a pretty stunning result. The time series looks really convincing. Is the way the detector itself is trained orthogonal to this or could there be some "leakage" in that the pre-chatgpt text is in the (positive) training data?

What detector are you using? How can you be sure of its accuracy given that every commercial AI detector has been debunked?

Could you share some pre LLM false positives? Would be interesting to see what is tripping the detection. Did a tiny fraction of authors write like LLMs, before LLMs?

A signal, I put an AI generated of mine (with heavy human guidance on aesthetics mostly and some minor human editing) and got 5% only.

Extend it to scan papers from pre-2020. That should give you a better baseline accuracy for your detection system.

this is neat! is the model available somewhere for local execution? or even a lookup table with your results for all arXiv pre-print codes? I want to run it on lots of pre-prints and I don't want to kill your server

Thank you for this work.