Unverified50% confidenceFactExact time
The independent and identically distributed (i.i.d.) assumption requires that each repeated run reinitialize the environment, fix sampling parameters, and keep the scorer version consistent; otherwise the pass rate is no longer an unbiased estimate and the Wilson lower bound loses meaning.
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
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Related Claims
UnverifiedExchangeability is a weaker requirement than independent and identically distributed (i.i.d.), requiring only that any permutation of the data points has the same joint probability distribution.73% similarUnverifiedThe prerequisite for this closed-form solution is a multivariate Gaussian distribution setting, and its direct applicability to strongly non-Gaussian, heavy-tailed, or highly nonlinear data should still be treated with caution.69% similarUnverifiedThe unweighted variant abandons the consistency guarantee and instead defines a self-consistent fixed-point condition: at the optimal solution the model-generated distribution coincides with the target distribution and the loss automatically takes a minimum value, and the fixed point can be approached through iterative updates.69% similarUnverifiedWhen the data distribution is balanced, D* approaches a certain baseline value, and the new formula reduces to a result close to the traditional formula; when the data are severely imbalanced or skewed, D* deviates significantly from the baseline, leading to large adjustments in the estimate of predictive performance.69% similarUnverifiedWriting only one position or conditionally independent positions per step can theoretically match the distribution exactly, while writing more dependent positions causes errors to accumulate.68% similar
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