Unverified50% confidenceFactExact time
A test item's English score has weak predictive power for its post-translation score, with a correlation coefficient of only 0.23, and only 0.27 on faithful translations; by contrast, the correlation coefficient between the English scores of the same test item before and after rewording reaches 0.48.
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10/15/2026
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UnverifiedIn manually proofread samples, the character error rate was only 0.68% when the text was clearly legible, but approximately 45% of sampled passages were completely uncorrectable due to source quality issues.68% similarUnverifiedAmong the five evaluators the authors tested, if the answer key had minor errors, the score was only 0.21 — lower than giving no key at all (0.46) and lower than giving a completely irrelevant key (0.50); while a human-verified model-generated answer scored 0.61, close to the 0.69 of a human-written one.68% similarUnverifiedIn open-ended generation tasks, the study observed occasional accuracy drops, which were more pronounced in non-English responses.67% similarUnverifiedAblation analysis shows that fine-tuning on the segment paradigm yields a +5.29-point improvement on the test set, while replacing the first 4,500 transcript words with 2,000 retrieved words yields only a +1.55-point improvement.65% similarUnverifiedThe language model's confidence is a self-assessed score (0 to 1), not a calibrated probability; the model may give high confidence to wrong answers and may give low scores to correct answers, so it should be treated as evidence rather than permission.64% similar
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