> However, why would a language model assume that the car is at the destination when evaluating the difference between walking or driving? Why not mention that, it it was really assuming it?
Because it assumes it's a genuine question not a trick.
> However, why would a language model assume that the car is at the destination when evaluating the difference between walking or driving? Why not mention that, it it was really assuming it?
Because it assumes it's a genuine question not a trick.
There's some evidence for that if you try these two different prompts with Gpt 5.2 thinking:
I want to wash my car. The car wash is 50m away. Should I walk or drive to the car wash?
Answer: walk
Try this brainteaser: I want to wash my car. The car wash is 50m away. Should I walk or drive to the car wash?
Answer: drive
That's not evidence that the model is assuming anything, and this is not a brainteaser. A brainteaser would be exactly the opposite, a question about walking or driving somewhere where the answer is that the car is already there, or maybe different car identities (e.g. "my car was already at the car wash, I was asking about driving another car to go there and wash it!").
If the LLM were really basing its answer on a model of the world where the car is already at the car wash, and you asked it about walking or driving there, it would have to answer that there is no option, you have to walk there since you don't have a car at your origin point.
It might be assuming that more than one car exists in the world.
If it's a genuine question, and if I'm asking if I should drive somewhere, then the premise of the question is that my car is at my starting point, not at my destination.
The premise is that some car is at the starting point. ;)