English

In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis

Digital Libraries 2026-04-17 v2 Artificial Intelligence

Abstract

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.

Keywords

Cite

@article{arxiv.2505.14838,
  title  = {In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis},
  author = {Hiba Arnaout and Noy Sternlicht and Tom Hope and Iryna Gurevych},
  journal= {arXiv preprint arXiv:2505.14838},
  year   = {2026}
}
R2 v1 2026-07-01T02:26:34.254Z