[stevenhuang]

It sounds feasible to detect cases of low temperature output, as the text output this way sounds very generic (like an average of all content seen near the prompt's latent space).

However once you prompt the LLM with a higher temperature, or tell it to roleplay as someone with elaborate personas, or suggest to use certain linguistic styles, or train it on example text... then it becomes much harder.

I imagine pathological cases of formulaic word use, sentence/paragraph structure will only be detectable in longer form text. After all text is already pretty low-resolution, not much for adversarial models to work with.