New ADVICE framework improves LLM confidence estimation by grounding it in answers

Researchers have developed a new framework called ADVICE to address overconfidence in large language models' verbalized confidence estimations. This framework aims to make confidence reporting more grounded in the model's actual answer, rather than being independent of it. Experiments indicate that ADVICE significantly improves confidence calibration and generalizes well to new scenarios without harming task performance. AI

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IMPACT Improves LLM trustworthiness by making confidence reporting more accurate and answer-dependent.

RANK_REASON Academic paper introducing a new framework for LLM confidence estimation.

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• ADVICE
• Ki Jung Seo
• arXiv

• paper
• safety