Grading the Graders: Verification Autonomy Levels (L0-L5) for LLM Reasoning
Large language models (LLMs) are increasingly paired with verifiers (step checkers, self-consistency filters, tool-based fact checkers, formal proof assistants) that claim to detect the model's errors. Yet the verification literature uses the word "level" to mean at least five different things: verification granularity, concept abstraction, risk tier, system-stack layer, and the epistemic source of the ground truth. We propose Verification Autonomy Levels (VAL), a meta-standard classifying verification schemes along a single axis: where does the verification spec come from, and what does the v
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- PossiblePossibly related (embedding) · 52%IEEE Rolls Out Large Language Models Virtual Training Course →
- FuzzyOverlapping authors or contributors · 62%rasbt/LLMs-from-scratch →
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- LinkedLinked via arxiv author · 85%Yajie Yin →
“Grading the Graders: Verification Autonomy Levels (L0-L5) for LLM Reasoning”