But the LLM predicts the output based on some notion of a likelihood so it could in principle signal if the likelihood of the returned token sequence is low, co

But the LLM predicts the output based on some notion of a likelihood so it could in principle signal if the likelihood of the returned token sequence is low, couldn’t it? Or do you mean that fine-tuning distorts these likelihoods so models can no longer accurately signal uncertainty?