There's no such thing as "llm hallucinations". For there to be there has to be an objective, rigorous way to distinguish them from non-hallucinations. Which doesn't exist. They walk like the "good" output, they quack like the "good" output, they are indistinguishable from the "good" output.

The only difference between the two is whether a human likes it. If the human doesn't like it, then it's a hallucination. If the human doesn't know it's wrong, then it's not a hallucination (as far as that user is concerned).

The term "hallucination" is just marketing BS. In any other case it'd be called "broken shit".

The term hallucination is used as if the network is somehow giving the wrong output. It's not. It's giving a probability distribution for the next token. Exactly what it was designed for. The misunderstanding is what the user thinks they are asking. They think they are asking for a correct answer, but they are instead asking for a plausible answer. Very different things. An LLM is designed to give plausible, not correct answers. And when a user asks for a plausible, but not necessarily correct, answer (whether or not they realize it) and they get a plausible but not necessarily correct answer, then the LLM is working exactly as intended.

Author here. You’ve just summarized the main part of the article. To keep things simple, the focus is on pure facts. But yes, the outcome of next token prediction is much more profound than wrong facts.