SOURCE-LINKED INTELLIGENCE
Beyond Semantic Accuracy: Consequence-Aware Evaluation for Safety-Critical Language Understanding
Can language models be trusted in safety- critical operations? In such settings, strong per- formance on semantic metrics does not guaran- tee operational reliability: a misread altitude, a dropped execution condition, or a confused call- sign may score well under standard F1 yet carry sharply asymmetric operational consequences. We study this problem in air traffic control (ATC), where controller-pilot communication demands near-zero error tolerance, and use consequence-aware evaluation to test whether semantic scores misstate operational reliabil- ity. The framework is instantiated in a con-
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T14:39:02.000Z
First collected: 2026-09-21T10:02:02.728Z. This is not the publication date.