发表机构
Massachusetts Institute of Technology（麻省理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用语义语言模型分析CORE数据库2015—2025年八个领域超26,000篇全文论文，发现2021年后论文与近期文献的文本相似度急剧上升，至2025年增长两倍多，表明科学写作在文本原创性维度上正逐渐失去独特性。
AI 中文摘要
科学产出正在快速增长，但尚不清楚不断扩大的文献是否保持原创，还是日益重复。原创性具有多个维度。其中一个维度现在可以直接衡量：一篇论文与先前工作相比在文本上的独特性。利用语义语言模型，我们筛选了CORE数据库（2015—2025年）中八个领域的超过26,000篇全文论文，查找与近期文献相似的段落。我们将每篇论文与固定大小的早期工作样本进行比较，因此相似度的增加并非文献增长的副产品。我们发现，一篇论文中与近期工作相似的文本比例在2021年前保持稳定，随后急剧上升，到2025年增长了两倍多。这一增长并非来自少数论文的更多借用，而是相似性在整个文献中的扩散：现在更多论文包含呼应近期工作的段落，且这一增长几乎不能由引用文献解释。我们还发现表达相同科学思想的段落出现了类似增长。这一模式在稳健性检验中保持一致，并在第二个独立数据库中得以复现。在这一可衡量的原创性维度上，科学写作与先前工作的区别已变得不那么明显。
英文摘要
Scientific output is growing rapidly, but it is unclear whether the expanding literature remains original or is increasingly repeating itself. Originality has many dimensions. One dimension can now be measured directly: how textually distinct a paper is from the work that came before it. Using semantic language models, we screened more than 26,000 full-text papers across eight fields in the CORE database (2015--2025) for passages resembling recent literature. We compared every paper against a fixed-size sample of earlier work, so increases in resemblance are not a by-product of literature growth. We find that the share of a paper's text resembling recent work was stable before 2021, then rose sharply, more than tripling by 2025. The increase came not from a few papers borrowing more heavily but from resemblance spreading across the literature: more papers now contain passages that echo recent work, and almost none of this growth is explained by cited work. We also found an analogous increase in passages expressing the same scientific idea. The pattern held across robustness checks and replicated in a second, independent database. Along this one measurable axis of originality, scientific writing has become less distinct from the work preceding it.
