Chain-of-Thought Can Hurt Performance on Tasks Where Thinking Makes Humans Worse

Re:Chain-of-Thought Can Hurt Performance on Tasks Where Thin... by thomashop on Thursday October 31, 2024 @03:30AM (#42004265)

Conversely, a pair of examples where it was incorrect hardly justifies the opposite response.

If you want a more scientific answer there is this recent paper: https://machinelearning.apple.com/research/gsm-symbolic

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Re:Chain-of-Thought Can Hurt Performance on Tasks Where Thin... by EraYaN on Thursday October 31, 2024 @06:28AM (#42005336)

It kind of does though, because it means you can never trust the output to be correct. The error is a much bigger deal than it being correct in a specific case.

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Re:Chain-of-Thought Can Hurt Performance on Tasks Where Thin... by thomashop on Thursday October 31, 2024 @10:10AM (#42007097)

You can never trust the outputs of humans to be correct but we find ways of verifying and correcting mistakes. The same extra layer is needed for LLMs.

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Re:Chain-of-Thought Can Hurt Performance on Tasks Where Thin... by digging on Thursday October 31, 2024 @11:09AM (#42007691)

> It kind of does though, because it means you can never trust the output to be correct.

Maybe some HN commenters will finally learn the value of uncertainty then.

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