检测并验证论文中虚构引用，提升学术可信度。
HalluCiteChecker: A Lightweight Toolkit for Hallucinated Citation Detection and Verification in the Era of AI Scientists
- 将虚假引用检测转化为NLP任务，提供轻量级工具包。
- 可在普通笔记本上秒级完成验证，全程离线运行。
- 适合审稿人、编辑和作者用于预审与发表前检查。
我们提出 HalluCiteChecker，一个用于检测和验证科学论文中虚构引用的工具包。随着AI辅助写作技术的发展，尽管引文推荐变得便捷，但虚假引用（即不存在的研究工作）也日益增多。这类引用不仅损害论文可信度，还增加了审稿人和作者手动核实的工作负担。本研究将虚假引用检测形式化为自然语言处理任务，并提供可实际应用的工具包作为解决方案基础。该工具包轻量高效，可在标准笔记本电脑上以秒级速度完成验证，支持完全离线运行，仅需CPU即可高效执行。我们希望 HalluCiteChecker 能减轻审稿工作量，助力会议组织者实现系统性预审与发表前核查。代码已开源，采用 Apache 2.0 许可，可通过 GitHub 和 PyPI 获取，附有 YouTube 演示视频。
原文摘要 · Abstract (English)
We introduce HalluCiteChecker, a toolkit for detecting and verifying hallucinated citations in scientific papers. While AI assistant technologies have transformed the academic writing process, including citation recommendation, they have also led to the emergence of hallucinated citations that do not correspond to any existing work. Such citations not only undermine the credibility of scientific papers but also impose an additional burden on reviewers and authors, who must manually verify their validity during the review process. In this study, we formalize hallucinated citation detection as an NLP task and provide a corresponding toolkit as a practical foundation for addressing this problem. Our package is lightweight and can perform verification in seconds on a standard laptop. It can also be executed entirely offline and runs efficiently using only CPUs. We hope that HalluCiteChecker will help reduce reviewer workload and support organizers by enabling systematic pre-review and publication checks. Our code is released under the Apache 2.0 license on GitHub and is distributed as an installable package via PyPI. A demonstration video is available on YouTube.
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