But then why does it stick to its guns on other questions but not this one?

I haven't played with this model, but rarely do I find working w/ Claude or GPT-4 for that to be the case. If you say it's incorrect, it will give you another answer instead of insisting on correctness.

It's how LLMs work in general.

If you find a case where forceful pushback is sticky, it's either because the primary answer is overwhelmingly present in the training set compared to the next best option or because there are conversations in the training that followed similar stickiness, esp. if the structure of the pushback itself is similar to what is found in those conversations.

Right... except you said:

> If you say it's incorrect, it will give you another answer instead of insisting on correctness.

> When you push it, it responds with the next most common answer.

Which clearly isn't as black and white as you made it seem.

I'll put it another way - behavior like this is extremely rare in my experience. I'm just trying to explain if one encounters it why it's likely happening.