通过细粒度时间引用分析，生成兼具褒贬的论文影响力摘要。
In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis
- 按引用意图分时序分析，区分肯定与修正类引用
- 人工评估显示摘要具备良好洞察力，相关性中到强
- 适合科研管理者与领域专家追踪研究演进
理解科学出版物的影响对于识别突破性成果和引导未来研究至关重要。传统基于引用次数的指标往往忽略论文在领域内贡献的细微差异。本文提出一项新任务：生成细致、富有表现力且具时间感知的影响力摘要，通过细粒度引用意图的演变，捕捉论文所获得的肯定（确认引用）与批评（更正引用）。我们构建了针对该任务的评估框架，在主观指标如洞察力上展现出中等到强的人工相关性。来自教授的专家反馈表明对这类摘要有强烈兴趣，并提出了未来改进方向。数据与代码已公开。
原文摘要 · Abstract (English)
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.
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