Unverified50% confidenceFactExact time
Calibration measures the degree of consistency between the confidence a model expresses and its actual accuracy.
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11/1/2026
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VerifiedCalibration means that the probabilities output by the model should match reality; neural networks generally have an overconfidence tendency, so model probabilities should not be blindly trusted, and thresholds should be set only after validation with labeled data.78% similarUnverifiedLaya's output includes answers with confidence scores, where the confidence score reflects the degree of certainty the model has in its current judgment, allowing downstream systems to decide whether to trigger manual review or escalate to a more powerful model.75% similarUnverified模型选型时应以每美元token产出或每瓦特推理性能替代单一准确率指标进行评估73% similarUnverifiedA model's stable performance across evaluation variants is more indicative of true alignment than a high score on a single evaluation; robustness rather than scores should be the focus.73% similarUnverifiedanswer_confidence is the probability the model assigns to the chosen option; confidence is a normalized measure of the concentration of the entire probability distribution.73% similar
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