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English(EN) Local Citation Recommendation Without Graph Signals

新的引文推荐系统绕过图偏见,提高准确性

研究人员开发了一种新的本地引文推荐(LCR)方法,该方法不依赖可能引入偏见的现有引文图。他们推出了本地引文推荐语料库(LCRC),这是一个包含14,735个来自天体物理学综述论文的科学陈述的数据集,每个陈述都有可访问的引文目标。与现有的密集检索基线相比,该新系统在Recall@25上提高了8.0%,在NDCG@25上提高了6.9%,且无需进行模型微调。代码和数据集均公开可用,以确保可复现性。 AI

影响 这项研究通过提供更准确、偏见更小的引文建议,有可能简化研究人员的文献综述过程。

排序理由 关于引文推荐新数据集和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.IR (Information Retrieval) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的引文推荐系统绕过图偏见,提高准确性

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
关于引文推荐新数据集和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
12 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Anna Kelbert ·

    无图信号的本地引用推荐

    Resolving correct citations can be a time-consuming task for research writers. We address local citation recommendation (LCR), where the goal is to retrieve appropriate references for a given sentence. Web tools generally depend on the existing citation graph, which may bias resu…