Unverified50% confidenceOpinionExact time
The article points out that the 50-sample evaluation set is too small, since gaining or losing a single sample can move accuracy by 2 percentage points, so the 86% result may simply reflect the model fitting these 50 samples rather than genuine generalization.
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10/18/2026
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UnverifiedOn a 50-sample evaluation set, an accuracy change from 74% to 76% corresponds to just one more correct sample, a difference that is statistically almost meaningless.79% similarUnverifiedThe gap between selection and generation exceeds 50 percentage points, revealing that reliability is far lower than benchmarks suggest when users need the model to directly write out kinship terms.77% similarUnverifiedTheoretically reliable clustered standard error estimation typically requires at least 30–50 clusters, whereas this study has only 19 independent time units, making the sample size relatively small.75% similarUnverified一个61分的模型和一个59分的模型在多数实际应用中的差异可能远小于分数暗示的程度75% similarUnverifiedUnder the condition of n=100 with an even split of positive and negative samples, the 95% confidence interval for 55% accuracy is roughly 45%–65%, which covers the 50% baseline, so the 5 percentage point gap may be random fluctuation.75% similar
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