We propose a toy model that shows how linear truth encodings can arise in language models.

Debate between AI experts outperforms single-advisor consultancy in helping humans make more accurate factual judgments, especially benefiting those with mainstream beliefs.

We propose a new method for LLMs to express uncertainty by adjusting the specificity of their responses.