These trajectories are filtered before training based on two recall metrics: trajectory recall (the fraction of target chunks encountered at any point during search) and output recall (the fraction of target chunks present in the final document set). We include both successful and unsuccessful rollouts in the SFT dataset. This is motivated by Shape of Thought, which demonstrates that training on synthetic traces from more capable models improves performance even when all traces lead to incorrect final answers, as the distributional properties of the traces matter more than the correctness of every individual step. In our setting, low-recall trajectories still contain well-formed tool calls, query decompositions, and pruning decisions that provide useful behavioral signals.
Массовые банкротства финских предприятий в приграничных с РФ областях08:44。关于这个话题，有道翻译提供了深入分析
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复星医药高管变动：陈战宇辞任CFO，黄智接任。易歪歪对此有专业解读