构建首个带修订指令的科学段落改写数据集，提升学术写作自动化质量。
ParaRev: Building a dataset for Scientific Paragraph Revision annotated with revision instruction
- 以段落级而非句子级为单位，结合详细修订指令进行文本优化。
- 实验表明，使用详细指令可显著提升自动改写质量，各指标均优于通用方法。
- 适合需要精准学术表达优化的研究者与AI写作工具开发者。
学术写作中的修改是关键环节，作者通过精炼内容以提升清晰度、结构和学术质量。现有自动化写作辅助多聚焦于句子级修改，难以捕捉有效修改所需的上下文信息。本文探索将科学文本修改任务从句子级扩展至段落级的意义。段落级任务能实现更深层次的改进，并在具体修订指令指导下完成。为此，我们提出ParaRev，首个包含科学段落改写及其人工标注修订指令的评估子集的数据集。实验表明，无论采用何种模型或评价指标，使用详细修订指令均显著提升自动化改写质量。
原文摘要 · Abstract (English)
Revision is a crucial step in scientific writing, where authors refine their work to improve clarity, structure, and academic quality. Existing approaches to automated writing assistance often focus on sentence-level revisions, which fail to capture the broader context needed for effective modification. In this paper, we explore the impact of shifting from sentence-level to paragraph-level scope for the task of scientific text revision. The paragraph level definition of the task allows for more meaningful changes, and is guided by detailed revision instructions rather than general ones. To support this task, we introduce ParaRev, the first dataset of revised scientific paragraphs with an evaluation subset manually annotated with revision instructions. Our experiments demonstrate that using detailed instructions significantly improves the quality of automated revisions compared to general approaches, no matter the model or the metric considered.
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