AI RESEARCH

Domain-level metacognitive monitoring in frontier LLMs: A 33-model atlas

arXiv CS.AI

ArXi:2605.06673v1 Announce Type: cross Aggregate metacognitive quality scores mask within-model variation across MMLU benchmark domains. We administered 1,500 MMLU items (250 per domain, under an a priori six-domain grouping) to 33 frontier LLMs from eight model families and computed Type-2 AUROC per model-domain cell using verbalized confidence (0-100). Total observations: 47,151. Every model with above-chance aggregate monitoring showed non-trivial domain-level variation.