Challenge: a recent study examines how far back in time we tend to cite papers . citation patterns are correlated with age, age, and other factors .
Approach: They analyze citation patterns across time and examine temporal changes . they find that 62% of cited papers are from the immediate five years prior to publication .
Outcome: The authors show that citing papers is the primary method of scientific writing . they show that the trend has reversed and current papers have low temporal diversity .

Similar Papers

Citation Amnesia: On The Recency Bias of NLP and Other Academic Fields (2025.coling-main)

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Challenge: citation age is a key factor in determining whether older works are cited in scientific journals or not.
Approach: They examine the tendency of NLP to cite older work across 20 fields of study over 43 years (1980–2023) . they put NLP’s propensity to citation older work in the context of these 20 other fields to see whether differences can be observed .
Outcome: The trend is strongest in NLP and ML research (-12.8% and -5.5% in citation age from previous peaks)
On Forgetting to Cite Older Papers: An Analysis of the ACL Anthology (2020.acl-main)

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Challenge: a growing number of published papers are citing older work, but the rate of citations is stable . a recent paper cited work from recent years, whereas papers published 15 or more years ago are cited at a stable rate.
Approach: They analyze citations in papers published at selected ACL venues between 2010 and 2019 . they find that recent papers are cited significantly more often in recent years .
Outcome: The authors analyze citations in journals and conferences between 2010 and 2019 . they find that recent papers cite more recent work, but papers published 15 or more years ago are cited at a stable rate.
Examining Citations of Natural Language Processing Literature (2020.acl-main)

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Challenge: citations of NLP papers have decreased in recent years, but long papers get three times as many citation as short papers . citation data from the ACL Anthology and Google Scholar can be used to understand the field and quantify the impact of different types of papers.
Approach: They extract data from the ACL Anthology and Google Scholar to examine trends in citations of NLP papers.
Outcome: The results show that only about 56% of the papers in AA are cited ten or more times . CL Journal has the most cited papers, but its citation dominance has lessened .
To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing (2023.emnlp-main)

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Challenge: Natural language processing (NLP) is in a period of disruptive change that is impacting our methodologies, funding sources, and public perception.
Approach: They conduct interviews with 26 NLP researchers of varying seniority, research area, institution, and social identity to identify cyclical patterns in the field and new shifts without historical parallel . they conclude by discussing shared visions, concerns, and hopes for the future of NLP .
Outcome: The authors identify cyclical patterns in the field, as well as new shifts without historical parallel, including changes in benchmark culture and software infrastructure.
A Systematic Review of Reproducibility Research in Natural Language Processing (2021.eacl-main)

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Challenge: Despite the recent progress in reproducibility, the field is far from reaching a consensus on how reproducibility should be defined, measured and addressed.
Approach: They propose to provide a wide-angle snapshot of current work on reproducibility in NLP.
Outcome: The proposed work will provide a wide-angle snapshot of current work on reproducibility in NLP.
Geographic Citation Gaps in NLP Research (2022.emnlp-main)

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Challenge: a vast number of papers accepted at top NLP venues come from a handful of western countries and (lately) China.
Approach: They ask researchers to examine the relationship between geographical location and publication success . they use a dataset of 70,000 papers from the ACL Anthology to examine their citation network .
Outcome: The proposed dataset of 70,000 papers from the ACL Anthology shows that there are substantial geographical disparities in paper acceptance and citations .
On the Gap between Adoption and Understanding in NLP (2021.findings-acl)

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Challenge: a recent paper argues that current publications foster a gap between adoption and understanding of models . it also makes it easier to meet publication demands with method papers, argues the paper .
Approach: They argue that current NLP publication models foster a gap between adoption and understanding of models . they argue that everlarger models make it harder to explain how our methods work .
Outcome: The authors argue that current publications foster a gap between adoption and understanding of models . they argue that the rise of everlarger models makes it harder to explain how our methods work .
The Nature of NLP: Analyzing Contributions in NLP Papers (2025.acl-long)

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Challenge: despite this, what constitutes NLP research remains debated .
Approach: They propose a taxonomy of research contributions and introduce a task of automatically identifying contribution statements and classifying their types from NLP research papers.
Outcome: The proposed model analyzes 29k NLP research papers to understand their contributions .
We are Who We Cite: Bridges of Influence Between Natural Language Processing and Other Academic Fields (2023.emnlp-main)

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Challenge: In this paper, we quantify the degree of influence between 23 fields of study and NLP (on each other)
Approach: They quantify the degree of influence between 23 fields of study and NLP on each other . they find that cross-field engagement of NLP has declined from 0.58 in 1980 to 0.31 in 2022 .
Outcome: The proposed Citation Field Diversity Index (CFDI) has declined from 0.58 in 1980 to 0.31 in 2022, the authors show .
NLP Scholar: A Dataset for Examining the State of NLP Research (2020.lrec-1)

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Challenge: Google Scholar is the largest web search engine for academic literature and provides access to rich metadata associated with the papers.
Approach: They extracted citation information from the ACL Anthology (AA) for about 44 thousand NLP papers and identified authors who published at least three papers there.
Outcome: The ACL Anthology (AA) is the largest repository of articles on Natural Language Processing (NLP).

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