Right, and then look at any number of research papers showing that CoT output has limited impact on the end result. We've trained these models to pretend to reason.
Right, and then look at any number of research papers showing that CoT output has limited impact on the end result. We've trained these models to pretend to reason.
If it's only pretending to reason, then how is it that the CoT output improves performance on every single benchmark/test?
> Right, and then look at any number of research papers showing that CoT output has limited impact on the end result.
Which research papers? Do I have to find them?
> We've trained these models to pretend to reason.
I have no idea why that matters. Can you tell me what the difference is if it looks exactly the same and has the same result?
When they say "pretends to" here they're talking about something quantifiable, that the extra text it outputs for CoT barely feeds back into the decisionmaking at all. In other words it's about as useful as having the LLM make the decision and then "explain" how it got there; the extra output is confabulation.
Though I'm not sure how true that claim is...
You make a good point. I had the impression they were using 'pretend' as a Chinese Room shortcut in that they are asserting that it is incapable of reasoning and only appears to be capable from the outside, which is completely irrelevant and unfalsifiable.