vminvsky

They never used a static detector.

i would recommend u read the paper. the contribution isnt a detector thats meant to be taken seriously; but a detector that works in a very specific task. they then use this to estimate use of LLMs on MTurk

according to the paper they get 98% accuracy. another recent paper came out saying it's always possible to discriminate between real and synthetic text [1].

i think the core problem is with the generalist classifiers (gptzero, openai detector, etc). ex. openai's classifier has an accuracy of around 25% on it's own text. however, when you train a bespoke classifier (like the authors did), you can get really good results.

[1] https://arxiv.org/pdf/2304.04736.pdf

It's actually pretty easy to create a bespoke ChatGPT detector!

What about double-descent :D