AI brief
A LessWrong post argues that no-CoT performance tracks base-model general intelligence and could soon drive automated research into architectures. It cites work on latent multi-hop reasoning by Ryan Greenblatt.
Why it matters: If no-CoT performance is a reliable measure of base-model intelligence, it could guide automated architecture search toward more capable and token-efficient reasoning models.
Written by AI from LessWrong's published text.
Source
“No-CoT performance has been a decent proxy for tracking the g-factor intelligence of base models (see work on latent multi-hop reasoning by Ryan Greenblatt ).”
Interpretation or community commentary rather than straight reporting.
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