Trained — weights learned from data by any training algorithm (SGD, Adam, evolutionary search, etc.). The algorithm must be generic — it should work with any model and dataset, not just this specific problem. This encourages creative ideas around data format, tokenization, curriculum learning, and architecture search.
Latin Extended scores highest because phonetic extensions are deliberately designed to resemble their Latin base forms. Mathematical Alphanumeric Symbols dominate the dataset (806 of 1,418 pairs) but score low because ornate mathematical letterforms (script, fraktur, double-struck) look nothing like plain Latin in a different font. Arabic scores lowest: the letterforms are structurally different from Latin even when confusables.txt maps them as confusable.
,详情可参考safew官方版本下载
Pull-through transforms,详情可参考同城约会
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