Verified75% confidenceFactExact time
Expected Calibration Error (ECE) bins prediction samples by confidence level, computes the weighted average of the difference between predicted confidence and actual accuracy within each bin, and ideally approaches 0.
3
Sources
75%
Confidence
Long-term
Relevance
7/8/2026
First Seen
Sources
元认知反馈：用强化学习让大模型准确表达不确定性
hackernewshackernews7/7/2026
Related Claims
Unverified研究者通常使用期望校准误差（ECE）来量化模型的校准程度82% similarUnverifiedThe Brier score assesses calibration quality by calculating the square of the difference between the predicted probability and the actual outcome, with a lower score indicating more accurate predictions69% similarUnverifiedWhen the number of match samples is sufficiently large, Elo ratings converge to the maximum likelihood estimate.68% similarVerifiedWhen samples are severely imbalanced, Accuracy becomes misleading—a model that predicts everyone as healthy can still achieve an accuracy of over 99%.67% similarUnverifiedEXPECT_FLOAT_EQ and EXPECT_DOUBLE_EQ perform comparisons based on ULP, tolerating a default deviation of 4 ULPs.67% similar
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