[s5ma6n]

To me it boils down to what is to be measured here. With logprobs we can measure both correctness and not attempted i.e. if LLM is guessing the response.

Similar to exams where both the progress to the solution and the final outcome/value of the calculations are part of the grade.

To have the cake and eat it too for chain-of-thought reasoning, one way is to ask for a "final answer" so the final response token logprobs can be evaluated https://chatgpt.com/share/67239d92-b24c-800a-af8c-40da7be1f5...

Another trick is using JSON mode to keep intermediate results and final response separate, so each can be graded accordingly.

[michaelt]

> one way is to ask for a "final answer" so the final response token logprobs can be evaluated

Alas, this won't work.

Imagine I ask an LLM to continue the sentence "Summing those up: 4+6.75+6.52=17.27 litres of pure alcohol. In summary, the total amount of pure alcohol they have is: "

The logprobs of the next token do not represent the LLM's confidence in its own answer. They represent the LLM's confidence in its ability to repeat the total from 18 words previously.