arXiv is the largest open-access repository for scientific literature. When submitting a paper, authors upload the manuscript's source files, from which the final PDF is compiled. These source files are also publicly downloadable, potentially exposing data unrelated to the published paper -- such as figures, documents, or comments -- that may unintentionally reveal confidential information or simply waste storage space. We thus ask ourselves: "What can be found within the source files of arXiv submissions?" We present a longitudinal analysis of ~600,000 submissions appeared on arXiv between 2015--2025. For each submission, we examine the uploaded source files to quantify and characterize data not required for producing the respective PDF. On average, 27% of the data in each submission are unnecessary, totaling >580 GB of redundant content across our dataset. Qualitative inspection reveals the presence of offensive/inappropriate text (e.g., "WTF does this mean?") and experimental details that could disclose ongoing research. We have contacted arXiv's leadership team, as well as the authors of affected papers to alert them of these issues. Finally, we propose recommendations and an automated tool to detect and analyze arXiv submissions residual data at scale, aiming to improve data hygiene in the arXiv's ecosystem.

翻译：arXiv是最大的科学文献开放获取存储库。作者提交论文时需上传稿件源文件，最终PDF由此编译生成。这些源文件同样可供公开下载，可能暴露出与已发表论文无关的数据——例如图表、文档或注释——这些数据可能无意中泄露机密信息，或仅仅是浪费存储空间。因此我们提出疑问：“arXiv提交的源文件中究竟存在哪些内容？”我们对2015年至2025年间出现在arXiv上的约60万份提交进行了纵向分析。针对每份提交，我们检查了上传的源文件，以量化并表征生成对应PDF所不需要的数据。平均而言，每份提交中27%的数据属于冗余内容，在我们的数据集中总计超过580GB。定性检查发现其中存在冒犯性/不当文本（例如“这他妈是什么意思？”）以及可能泄露在研项目的实验细节。我们已联系arXiv管理团队及相关论文作者以提醒这些问题。最后，我们提出建议并开发了一款自动化工具，用于大规模检测分析arXiv提交的残留数据，旨在改善arXiv生态系统中的数据卫生状况。