zlacker

>>koie+(OP)
I've also noticed LLMs seem to lack conviction on the correctness of their answers. As the paper notes, you can easily convince the transformer that a correct answer is wrong, and needs adjustment. Ultimately they're just trying to please you. For example with ChatGPT 3.5 (abbreviated):

me: what is sin -pi/2

gpt: -1

me: that's not right

gpt: I apologize, let me clarify, the answer is 1

>>pton_x+zB
I just re-ran this on GPT-4 and it apologized, told me I was right, and then said again that the answer was -1. So while it lacked conviction it at least kept the correct answer.