LLM-as-a-Verifier Frames Verification as a New Scaling Axis

arXiv·high signal

Argues that verification — deciding whether a solution is correct — is a distinct capability axis alongside pre-training, post-training, and test-time compute, and builds a general-purpose verifier framework to exploit it. Relevant to anyone using LLM-as-judge, best-of-N selection, or self-consistency. The implication is that spending compute on a stronger verifier can beat scaling the generator.