Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification

Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov +9

Large language models (LLMs) are notorious for hallucinating, i.e., producing erroneous claims in their output. Such hallucinations can be dangerous, as occasional factual inaccura…