Answer correctness and question answerability are separate axes: ordinary confidence tracks the first while hidden probes track the second, and a factorized dual-threshold policy certifies both risk budgets at higher correct-answer coverage.
Do large language models know what they don’t know? InFindings of the Association for Computational Linguistics: ACL 2023, pp
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Two Axes of LLM Abstention: Answer Correctness and Question Answerability
Answer correctness and question answerability are separate axes: ordinary confidence tracks the first while hidden probes track the second, and a factorized dual-threshold policy certifies both risk budgets at higher correct-answer coverage.