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一篇实验性博客文章提出「Bag of Decisions」重排方法：让 LLM 为每个查询生成一组是/否判准问题，再用 Jev 计算各问题为真的概率并求和作为相关性分数，在 Wayfair WANDS 和 Amazon ESCI 数据集上均优于 BM25 和单一问题重排。
This paper introduces a decision-focused learning approach for survival analysis that aligns predictive models with downstream allocation decisions, using NDCG optimization. Applied to US heart transplant data, it improves ranking performance by 50-100%, potentially yielding thousands of additional life-years annually.