[viraptor]

Then don't use any website - 100% false positives. But seriously, it's a 9% rate for specific models at the time. It's a cat and mouse game and any fine tuning or a new release will throw it off. Also they don't say which 9% was misclassified, but I suspect it's the most important ones - the well written articles. If I see a dumb tweet with a typo it's unlikely to come from LLM (and if it does, who cares), but a well written long form article may have been slightly edited with LLM and get caught. The 9% is not evenly distributed.

[benreesman]

It was a cat and mouse game before, spam always is. The inevitable reality that spam is a slog of a war isn’t a good argument for giving up.

I don’t know the current meta on LLM vs LLM detector, but if I had to pick one job or the other, I’d rather train a binary classifier to detect a giant randomized nucleus sampling decoder thing than fool a binary classifier with said Markov process thing.

Please don’t advocate for giving up on spam, that affects us all.