@okayyeahwhatever It just doesn't know when to stop. got better at it though. early chatgpt was way overfit to that style and now it's just overfit to other things that are harder to detect. Some very good developers for example warn against this. It produces fewer obvious bugs than it once did, but it produces some that are extremely hard to detect because they are so dissimilar to how humans reason, yet the code is optimized to look highly human. similar to the chat output. Fable has a 50% hallucination rate for things it doesn't know. If you ask it to provide sources for the claims it has compiled into a document, at least 4/10 statements in my experience have an incorrect source attached to it.
This looks extremely like a well-researched human document, because a sloppily-researched human document has FEWER footnotes and NONE for the things that are ass pulls.
An LLM instead behaves like an insanely brazen liar and just puts hundreds of citations everywhere. No human is going to check all of them.