Unverified50% confidenceFactExact time
Many models still exhibit high confidence in incorrect answers, presenting a confidence calibration problem.
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9/11/2026
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Related Claims
UnverifiedThe academic community refers to the phenomenon of significant deviation between a model's confidence and its actual accuracy as Poor Calibration.76% similarUnverifiedDeep learning models are generally prone to overconfidence, where the probability values output by a model do not truly reflect the actual probability of its predictions being correct — a phenomenon known as poor calibration.75% similarUnverifiedPrecision bias refers to the tendency for people to assign higher credibility to statements containing precise numbers; experiments show that subjects rated the credibility of "41.3%" significantly higher than "approximately 40%".73% similarVerifiedWhen samples are severely imbalanced, Accuracy becomes misleading—a model that predicts everyone as healthy can still achieve an accuracy of over 99%.71% similarUnverifiedThe 2023 TruthfulQA benchmark showed that even the strongest models at the time did not exceed 60% accuracy on questions requiring precise factual judgment.71% similar
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