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Calibration accuracy is a key metric for evaluating an agent's decision quality under uncertainty; it not only examines whether the final answer is correct but also measures whether confidence matches the true probability of correctness.
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10/20/2026
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UnverifiedCalibration refers to the degree to which a model's expressed confidence matches the actual frequency of correctness, and is commonly quantified using reliability diagrams and Expected Calibration Error (ECE).76% similarUnverifiedResult validation requires establishing objective quantitative standards—such as classification accuracy, reply compliance, and manual correction ratio—and calculating statistics over a sufficient sample size.75% similarUnverifiedThe model's confidence is calibrated, trained via reinforcement learning with strict scoring rules, statistically aligning output probabilities with actual accuracy.74% similarUnverifiedA useful decision benchmark should simultaneously report both accuracy and calibration, ensure that evaluation questions match deployment questions, and be able to distinguish strong from weak systems.74% similarUnverified校准性（Calibration）指模型表达的置信度与实际准确率之间的一致程度，是评估AI模型质量的核心指标之一73% similar
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