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Summary:
内容总结:该研究提出了一种知识图谱提示方法(KGP),用于多文档问题回答(MD-QA)。该方法通过构建知识图谱,将多个文档中的段落和文档结构作为节点,并通过语义或词汇相似性以及文档结构关系作为边进行连接。然后,设计了一种基于大型语言模型(LLM)的图遍历代理,以选择性地访问最有可能的节点,从而逐步接近问题并提高检索质量。实验结果显示,KGP在MD-QA任务中表现出色,特别是在需要跨文档推理和检索的情况下,显现出利用图结构提升提示设计和增强生成的潜力。
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Next Reading:
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Summary:
内容总结:该研究提出了一种知识图谱提示方法(KGP),用于多文档问题回答(MD-QA)。该方法通过构建知识图谱,将多个文档中的段落和文档结构作为节点,并通过语义或词汇相似性以及文档结构关系作为边进行连接。然后,设计了一种基于大型语言模型(LLM)的图遍历代理,以选择性地访问最有可能的节点,从而逐步接近问题并提高检索质量。实验结果显示,KGP在MD-QA任务中表现出色,特别是在需要跨文档推理和检索的情况下,显现出利用图结构提升提示设计和增强生成的潜力。
Resource:
Paper information:
Notes:
Model Graph:
Result::
Thoughts:
Next Reading:
The text was updated successfully, but these errors were encountered: