> However, LLMs are not able to autoformalize reliably, so they got them to autoformalize each problem many times. Some of the formalizations were correct, but even the incorrect ones were useful as training data, as often they were easier problems.
So didn't actually solve autoformalization, which is why they still needed humans to translate the input IMO 2024 problems.
The reason why formalization is harder than you think is that there is no way to know if you got it right.
You can use Reinforcement Learning with proofs and have a clear signal from the proof checker.
We don't have a way to verify formalizations the same way.
> However, LLMs are not able to autoformalize reliably, so they got them to autoformalize each problem many times. Some of the formalizations were correct, but even the incorrect ones were useful as training data, as often they were easier problems.
So didn't actually solve autoformalization, which is why they still needed humans to translate the input IMO 2024 problems.
The reason why formalization is harder than you think is that there is no way to know if you got it right. You can use Reinforcement Learning with proofs and have a clear signal from the proof checker. We don't have a way to verify formalizations the same way.