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English(EN) ScholarSum: Student-Teacher Abstractive Summarization via Knowledge Graph Reasoning and Reflective Refinement

ScholarSum框架利用知识图谱增强科学论文摘要

研究人员推出ScholarSum,一个旨在改进科学文献抽象摘要的新框架。该系统采用师生方法,利用分层知识图谱来捕捉文档的全局逻辑和主题。学生模型生成初稿,然后由类似教师的审阅者进行精炼,通过迭代检索和重写来识别和纠正不支持的内容。实验表明,ScholarSum在完整性和事实一致性方面均优于现有方法。 AI

影响 该框架可以显著提高研究人员理解科学文献的效率和准确性。

排序理由 该集群描述了一篇关于用于抽象摘要的新颖框架的详细研究论文。

在 arXiv cs.IR (Information Retrieval) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

ScholarSum框架利用知识图谱增强科学论文摘要

报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Bohou Zhang, Xiaoyu Tao, Mingyue Cheng, Huijie Liu, Qi Liu ·

    ScholarSum: Student-Teacher Abstractive Summarization via Knowledge Graph Reasoning and Reflective Refinement

    arXiv:2606.18850v1 Announce Type: new Abstract: Abstractive summarization plays a crucial role in enabling efficient understanding of scientific literature, yet it inherently demands both linguistic fluency and factual faithfulness. Existing approaches often fail to reconcile the…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Qi Liu ·

    ScholarSum:通过知识图谱推理和反思性精炼实现师生抽象式摘要

    Abstractive summarization plays a crucial role in enabling efficient understanding of scientific literature, yet it inherently demands both linguistic fluency and factual faithfulness. Existing approaches often fail to reconcile these two requirements. Extractive methods rely on …