English(EN) Zero-Cost Detection of Fabricated Citations: A Staged Heuristic Approach for Computing Dissertation Assessment

新框架利用大型语言模型检测伪造的学术引文

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-23 04:00

研究人员开发了一个名为“伪造严重性堆栈”（Fabrication Severity Stack, FSS）的新框架，用于识别学术作品中的伪造引文。这个三层系统根据检测难度对引文伪造进行分类，从完全不存在的参考文献到更微妙的错误归属。所提出的方法采用分阶段启发式工作流程，可以使用标准的大型语言模型接口实现，为教育工作者提供了一种实用的、零成本的解决方案，用于将参考文献验证整合到学位论文和报告评估中。初步测试表明，该方法可以有效地标记不存在的参考文献并检测到一些元数据损坏。 AI

影响为教育工作者提供了一种零成本的方法来打击人工智能生成的学术不端行为。

排序理由学术论文，提出新框架和方法论。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

本文如何被排名

Signal score: 5 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 学术论文，提出新框架和方法论。[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, safety; 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: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Hazrat Ali, Mohamed Elawady · 2026-10-23 04:00

Zero-Cost Detection of Fabricated Citations: A Staged Heuristic Approach for Computing Dissertation Assessment

arXiv:2610.28649v1 Announce Type: cross Abstract: Generative AI's growing role in academic writing has driven a rise in fabricated references across dissertations and student reports. We present the Fabrication Severity Stack (FSS), a three-tiered framework classifying citation f…

本文如何被排名

报道来源 [1]

Zero-Cost Detection of Fabricated Citations: A Staged Heuristic Approach for Computing Dissertation Assessment

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