Understanding the impact of scientific publications is crucial for identifying breakthroughs and guiding future research. Traditional metrics based on citation counts often miss the nuanced ways a paper contributes to its field. In this work, we propose a new task: generating nuanced, expressive, and time-aware impact summaries that capture both praise (confirmation citations) and critique (correction citations) through the evolution of fine-grained citation intents. We introduce an evaluation framework tailored to this task, showing moderate to strong human correlation on subjective metrics such as insightfulness. Expert feedback from professors reveals a strong interest in these summaries and suggests future improvements. Data and code are made available.

翻译：理解科学出版物的影响对于识别突破性进展和指导未来研究至关重要。基于引用次数的传统指标往往忽略了论文对研究领域产生的细腻贡献。本文提出一项新任务：通过细粒度引文意图的演变，生成兼具褒扬（确认性引用）与批评（修正性引用）的细腻、表达性强且具有时间感知力的影响总结。我们针对该任务构建了专属评估框架，在洞察力等主观指标上显示出中等至强的人类相关性。教授专家的反馈表明，这类总结具有强烈吸引力，并提出了未来改进方向。相关数据与代码已公开。