Mechanistic experiments on Gemma 3 27B, Qwen 2.5 7B and Magistral Small 24B show verbal confidence is cached at post-answer positions from answer tokens and captures richer answer-quality information beyond token log-probabilities.
arXiv preprint arXiv:2510.05126 (2025)
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Meta-d' and signal detection theory provide quantitative tools to assess metacognitive sensitivity and risk-based regulation in large language models.
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How do LLMs Compute Verbal Confidence
Mechanistic experiments on Gemma 3 27B, Qwen 2.5 7B and Magistral Small 24B show verbal confidence is cached at post-answer positions from answer tokens and captures richer answer-quality information beyond token log-probabilities.
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Measuring the metacognition of AI
Meta-d' and signal detection theory provide quantitative tools to assess metacognitive sensitivity and risk-based regulation in large language models.