SOURCE-LINKED INTELLIGENCE

Risk Is Not Review Value: Wrong-Answer Exposure Under Bounded Review Budgets

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

LLM assistants often produce more answers than humans can review before users see them. Most evaluations ask whether an answer is wrong, unsupported, or low-confidence. Bounded review budgets instead ask which answers should be checked first under a fixed review budget. Risk alone is not enough: a high-risk answer may be hard to repair, while a moderately risky answer may be directly correctable from available evidence. For generated-answer evaluation, we model review prioritization as exposure reduction, where review value combines estimated wrongness, intervention affordance, impact, and cos

Read original source ↗ Open in workspace

recordType

paper

region

Global