AI RESEARCH
LLMs as Signal Detectors: Sensitivity, Bias, and the Temperature-Criterion Analogy
arXiv CS.AI
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ArXi:2603.14893v1 Announce Type: cross Large language models (LLMs) are evaluated for calibration using metrics such as Expected Calibration Error that conflate two distinct components: the model's ability to discriminate correct from incorrect answers (sensitivity) and its tendency toward confident or cautious responding (bias). Signal Detection Theory (SDT) decomposes these components.