发表机构
University of Auckland; Abilene Christian University; Aalto University（奥克兰大学; 阿比林基督教大学; 阿尔托大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过分析ACM数字图书馆中计算机教育文献的引用趋势，发现LLM生成的幻觉参考文献虽仍罕见但增长迅速，构成学术诚信风险。
AI 中文摘要
准确的参考文献是学术工作的基础，能够实现验证、归属和系统综述。然而，大型语言模型的快速普及引入了一个严重的诚信问题：看似合理但虚构的引用。尽管幻觉参考文献被广泛讨论，但它们在特定研究社区中的可见性仍不清楚。我们通过使用ACM数字图书馆数据，检查关键计算机教育场所的参考文献完整性来解决这一差距。我们分析了24,751篇计算机教育论文中的引用趋势，并将其与更广泛的ACM语料库（超过723,000篇论文和1500万条参考文献）进行比较。然后，我们检查这些场所的参考文献列表，对常见的书目错误进行分类，并手动识别包含可验证虚假信息的LLM生成的幻觉，包括不可能的页码范围、虚构的标题和错误归属的作者。2025年，幻觉参考文献出现在五个SIGCSE主办或合作的场所。仅在技术研讨会上，经过验证的幻觉参考文献从2025年的3篇增加到2026年的17篇，出现在2026年会议论文集的2.3%中。尽管目前仍相对罕见，但这种增长构成了我们社区不应忽视的诚信风险。
英文摘要
Accurate references are foundational to scholarly work, enabling verification, attribution, and systematic review. However, the rapid adoption of large language models has introduced a serious integrity concern: plausible-looking but fabricated citations. Although hallucinated references are widely discussed, their visibility within specific research communities remains unclear. We address this gap by examining reference integrity at key computing education venues using ACM Digital Library data. We analyze referencing trends across 24,751 computing education papers and compare them with the broader ACM corpus of more than 723,000 papers and 15 million references. We then examine reference lists from these venues, classify common bibliographic errors, and manually identify LLM-generated hallucinations containing verifiably false information, including impossible page ranges, invented titles, and misattributed authors. In 2025, hallucinated references appeared across five SIGCSE-sponsored or in-cooperation venues. At the Technical Symposium alone, verified hallucinated references increased from 3 in 2025 to 17 in 2026, appearing in 2.3\% of 2026 proceedings papers. Although still relatively rare for now, this growth poses an integrity risk our community should not ignore.
CommentsAccepted to SIGCSE Technical Symposium 2027
