@inproceedings{arnaout-etal-2026-depth,
title = "In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis",
author = "Arnaout, Hiba and
Sternlicht, Noy and
Hope, Tom and
Gurevych, Iryna",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.acl-long.307/",
pages = "6749--6789",
ISBN = "979-8-89176-390-6",
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."
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%0 Conference Proceedings
%T In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis
%A Arnaout, Hiba
%A Sternlicht, Noy
%A Hope, Tom
%A Gurevych, Iryna
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-390-6
%F arnaout-etal-2026-depth
%X 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.
%U https://aclanthology.org/2026.acl-long.307/
%P 6749-6789
Markdown (Informal)
[In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis](https://aclanthology.org/2026.acl-long.307/) (Arnaout et al., ACL 2026)
ACL