This is a good reframe. The intermediate reasoning steps being "wrong" doesn't matter if the final output is correct. It's similar to how humans think through problems, lots of wrong turns before the right answer. The error compounding argument assumes each token is a final
Intermediate Reasoning Steps in AI Models and Error Tolerance
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