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ARXIV:2604.16009 · AI METACOGNITION · SUBMITTED 20 APR · 20:24 UTC · FRESHNESS STALE
ARXIV:2604.16009AI METACOGNITIONSUBMITTED 20 APR · 20:24 UTCFRESHNESS STALEFarhad Abtahi · Abdolamir Karbalaie · Eduardo Illueca-Fernandez · Fernando Seoane · arXiv
MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement.
Opportunity summary
Pain MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement.
Evidence 0 refs | 3 sources | 50% coverage
Blocker Evidence unverified
MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement. We introduce MEDLEY-BENCH, a benchmark of behavioural metacognition that separates independent…
Metacognition, the ability to monitor and regulate one's own reasoning, remains under-evaluated in AI benchmarking. We introduce MEDLEY-BENCH, a benchmark of behavioural metacognition that separates independent reasoning, private self-revision, and socially influenced revision under…
ScienceToStartup currently rates this 5.0/10 on the public viability pass. Results show a robust evaluation/control dissociation: evaluation ability increases with model size within families, whereas control does not. Code availability is flagged in the…
AI Metacognition moved forward this cycle; last verified April 2026. Public score 5.0/10. Production flags indicate code availability.
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MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement.
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10.48550/arXiv.2604.16009MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement.
Abstract
Metacognition, the ability to monitor and regulate one's own reasoning, remains under-evaluated in AI benchmarking. We introduce MEDLEY-BENCH, a benchmark of behavioural metacognition that separates independent reasoning, private self-revision, and socially influenced revision under genuine inter-model disagreement. The benchmark evaluates 35 models from 12 families on 130 ambiguous instances across five domains and reports two complementary scores: the Medley Metacognition Score (MMS), a tier-based aggregate of reflective updating, social robustness, and epistemic articulation, and the Medley Ability Score (MAS), derived from four metacognitive sub-abilities. Results show a robust evaluation/control dissociation: evaluation ability increases with model size within families, whereas control does not. In a follow-up progressive adversarial analysis of 11 models, we observed two behavioural profiles, i.e., models that revise primarily in response to argument quality and models that track consensus statistics. Under within-model relative profiling (ipsative scoring), evaluation was the weakest relative ability in all 35 models, indicating a systematic knowing/doing gap. Smaller and cheaper models often matched or outperformed larger counterparts, suggesting that metacognitive competence is not simply a function of scale. These findings position MEDLEY-BENCH as a tool for measuring belief revision under social pressure and suggest that future training should reward calibrated, proportional updating rather than output quality alone.
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PROBLEM
MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement. We introduce MEDLEY-BENCH, a benchmark of behavioural metacognition that separates independent reasoning, privat...
METHOD
Metacognition, the ability to monitor and regulate one's own reasoning, remains under-evaluated in AI benchmarking. We introduce MEDLEY-BENCH, a benchmark of behavioural metacognition that separates independent reasoning, private self-revision, and socially influenced revision u...
RESULT
ScienceToStartup currently rates this 5.0/10 on the public viability pass. Results show a robust evaluation/control dissociation: evaluation ability increases with model size within families, whereas control does not. Code availability is flagged in the production record; the pu...
WHY NOW
AI Metacognition moved forward this cycle; last verified April 2026. Public score 5.0/10. Production flags indicate code availability.
Abstract-backed public claims while anchored extraction refreshes.
MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement. We introduce MEDLEY-BENCH, a benchmark of behavioural metacognition that separates independent reasoning, private self-revision, and socially influenced revision under genuine inter-model disagreement.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Metacognition, the ability to monitor and regulate one's own reasoning, remains under-evaluated in AI benchmarking. We introduce MEDLEY-BENCH, a benchmark of behavioural metacognition that separates independent reasoning, private self-revision, and socially influenced revision under genuine inter-model disagreement.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 5.0/10 on the public viability pass. Results show a robust evaluation/control dissociation: evaluation ability increases with model size within families, whereas control does not. Code availability is flagged in the production record; the public repository link still needs proof alignment.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
AI Metacognition moved forward this cycle; last verified April 2026. Public score 5.0/10. Production flags indicate code availability.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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MEDLEY-BENCH is a new benchmark for AI metacognition that reveals a dissociation between evaluation ability and control, showing scale does not guarantee improvement.
Segment
AI Metacognition
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partial
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