Researchers have developed HalluCiteChecker, a novel toolkit designed to detect and verify hallucinated citations in academic papers. This tool addresses the challenge posed by AI-assisted citation recommendations that can lead to the inclusion of non-existent citations, which damage the credibility of scientific literature. The authors formalize the detection of hallucinated citations as a natural language processing (NLP) task, providing a lightweight solution that operates efficiently on standard laptops without requiring internet access. The toolkit aims to alleviate the verification burden on authors and reviewers by enabling systematic checks prior to publication. HalluCiteChecker is available as an open-source package on GitHub and can be installed via PyPI, with a demonstration video accessible on YouTube.
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Introducing HalluCiteChecker: A Toolkit for Detecting Hallucinated Citations in Scientific Papers
arXiv AI· Yusuke Sakai, Hidetaka Kamigaito, Taro Watanabe· Friday, May 1, 2026
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