← 研踪 PaperTrailarXiv:2611.15797 · v1
Early Reflections on How Large Language Models are Reshaping Software Engineering Research
首次提交 2026-11-12 02:10
版本更新 2026-11-12 02:10
雷达观测 2026-11-13 14:16
摘要
Large language models (LLMs) are radically reshaping software engineering (SE) research. Yet, their steep financial and computational costs raise questions about who participates in that change, and who does not. By analysing all 1,918 papers published in the ICSE 2019-2026 Research and SEIP tracks, we uncover a shifting and highly concentrated research landscape. China and the US dominate LLM-based SE research, appearing in 74% of LLM-based publications between 2023-2026, yet they diverge sharply in their use of commercial versus open-weight models. Beneath this national dominance lies extreme institutional concentration: just 5 institutions in China and 7 in the US appear in more than half of their respective nations' LLM-based output. In the US, only half of the unique institutions active in 2023-2026 participated in LLM-based research, whereas Singapore displays broader usage, with 11 of 15 active institutions participating in LLM-based work. Furthermore, across 2023-2026 Research-track papers, industry involvement is more prevalent in LLM-based work (23.4% vs 16.9%), and academia-only papers make up a smaller share (63.4% vs 70.9%). Crucially, we expose a gap in model usage across industry and academia. SEIP track papers lean strongly towards commercial LLMs, with 77.4% featuring them and 40.5% using them exclusively. In contrast, only 21.2% of Research-track work relies strictly on commercial models, making greater use of open-weight models that typically support more sustainable and reproducible experiments. However, this divide warrants reflection on the extent to which SE research aligns with industry practice.
作者备注：5 pages, 2 figures, 1 table
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v1 · 2026-11-12 02:10 · 最新观测版本
Early Reflections on How Large Language Models are Reshaping Software Engineering Research
Large language models (LLMs) are radically reshaping software engineering (SE) research. Yet, their steep financial and computational costs raise questions about who participates in that change, and who does not. By analysing all 1,918 papers published in the ICSE 2019-2026 Research and SEIP tracks, we uncover a shifting and highly concentrated research landscape. China and the US dominate LLM-based SE research, appearing in 74% of LLM-based publications between 2023-2026, yet they diverge sharply in their use of commercial versus open-weight models. Beneath this national dominance lies extreme institutional concentration: just 5 institutions in China and 7 in the US appear in more than half of their respective nations' LLM-based output. In the US, only half of the unique institutions active in 2023-2026 participated in LLM-based research, whereas Singapore displays broader usage, with 11 of 15 active institutions participating in LLM-based work. Furthermore, across 2023-2026 Research-track papers, industry involvement is more prevalent in LLM-based work (23.4% vs 16.9%), and academia-only papers make up a smaller share (63.4% vs 70.9%). Crucially, we expose a gap in model usage across industry and academia. SEIP track papers lean strongly towards commercial LLMs, with 77.4% featuring them and 40.5% using them exclusively. In contrast, only 21.2% of Research-track work relies strictly on commercial models, making greater use of open-weight models that typically support more sustainable and reproducible experiments. However, this divide warrants reflection on the extent to which SE research aligns with industry practice.
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