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For temporal predictions, conventional classification approaches proved inadequate since they treat time intervals as separate categories. Instead, the team implemented continuous numerical tokenization with mean-squared error optimization, teaching the model to recognize time as a continuous spectrum. This architectural decision yielded substantially improved accuracy—reducing median prediction error to 87 months compared to 178 months using standard regression techniques and 180 months using naive age-assumption baselines.
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Fixed bottom prompt row (moongate) when running in an interactive terminal.。关于这个话题，搜狗输入法提供了深入分析