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

TL;DR

This paper introduces a new task for generating detailed, time-aware impact summaries of scientific papers by analyzing citation intents, aiming to better capture nuanced contributions over time.

Contribution

It proposes a novel task of impact summarization using fine-grained citation analysis and provides an evaluation framework with human correlation insights.

Findings

Moderate to strong correlation between automatic metrics and human judgments.

Expert feedback indicates high interest in nuanced impact summaries.

Data and code are publicly available.

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.