E-SENS: Exclusion-Sensitive Penalization for Negative-Constraint Retrieval
研究人员提出了一种名为 E-SENS 的无需训练重排序方法，用于解决检索增强语言模型在负约束检索中忽略用户排除概念的问题。该方法通过提取针对被排除侧的紧凑陷阱查询，并从原始查询检索分数中减去该相似度得分。在 ExcluIR 基准测试中，E-SENS 在四种嵌入模型上均显示出明确的召回违背权衡关系，并在保持召回率的同时有效减少了陷阱检索。
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Researchers published a new paper on arXiv, proposing a method called E-SENS (Exclusion-Sensitive Penalization). This method aims to address the performance degradation in negative constraint retrieval tasks caused by ignoring excluded items. By introducing a sensitivity penalty mechanism for exclusion conditions, E-SENS can more accurately handle query scenarios containing negative information, thereby improving the accuracy and reliability of the retrieval system.
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