We are Who We Cite: Bridges of Influence Between Natural Language Processing and Other Academic Fields (2023.emnlp-main)
Copied to clipboard
| 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 . |
Similar Papers
Examining Citations of Natural Language Processing Literature (2020.acl-main)
Copied to clipboard
| 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 . |
Internal and External Impacts of Natural Language Processing Papers (2025.acl-short)
Copied to clipboard
| Challenge: | a new study examines the impact of NLP research published in top-tier conferences from 1979 to 2024 . language modeling has the widest internal and external influence, while linguistic foundations have lower impacts . |
| Approach: | They analyze citations from research articles and external sources to determine how NLP topics are consumed internally and externally. |
| Outcome: | The findings show that language modeling has the widest internal and external influence . ethics, bias, and fairness show significant attention in policy documents with fewer academic citations . |
Citation Amnesia: On The Recency Bias of NLP and Other Academic Fields (2025.coling-main)
Copied to clipboard
| 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) |
The Nature of NLP: Analyzing Contributions in NLP Papers (2025.acl-long)
Copied to clipboard
| 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 . |
To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing (2023.emnlp-main)
Copied to clipboard
| 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. |
Collaboration or Corporate Capture? Quantifying NLP’s Reliance on Industry Artifacts and Contributions (2024.acl-long)
Copied to clipboard
| Challenge: | EMNLP 2022 citations are three times greater than expected for pre-trained models . industry participation in the Association of Computational Linguistics (ACL) anthology has increased 180% from 2017 to 2022. |
| Approach: | They surveyed 100 papers published at EMNLP 2022 to determine the ratio of their citations to industry models. |
| Outcome: | a new study shows that industry citations are three times greater than expected . the study aims to better understand whether industry collaboration is still collaboration . industry participation in the 2023 AI index report is the top takeaway . |
The Elephant in the Room: Analyzing the Presence of Big Tech in Natural Language Processing Research (2023.acl-long)
Copied to clipboard
Mohamed Abdalla, Jan Philip Wahle, Terry Ruas, Aurélie Névéol, Fanny Ducel, Saif Mohammad, Karen Fort
| Challenge: | Recent advances in deep learning methods for natural language processing (NLP) have created new business opportunities and made NLP research critical for industry development. |
| Approach: | They examine industry presence in the field since the early 90s and characterize it using a corpus of 78,187 NLP publications and 701 resumes of NLP publication authors. |
| Outcome: | The authors find that industry presence among NLP authors has been steady before a steep increase over the past five years (180% growth from 2017 to 2022). |
NLP Scholar: A Dataset for Examining the State of NLP Research (2020.lrec-1)
Copied to clipboard
| 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). |
Defining a New NLP Playground (2023.findings-emnlp)
Copied to clipboard
Sha Li, Chi Han, Pengfei Yu, Carl Edwards, Manling Li, Xingyao Wang, Yi Fung, Charles Yu, Joel Tetreault, Eduard Hovy, Heng Ji
| Challenge: | Recent explosion of performance of large language models (LLMs) has changed the field more abruptly and seismically than any other shift in the field’s 80 year history. |
| Approach: | They propose 20+ PhD-dissertation-worthy research directions to define a new NLP playground by combining theoretical analysis, new and challenging problems, learning paradigms and interdisciplinary applications. |
| Outcome: | The proposed research will cover theoretical analysis, new and challenging problems, learning paradigms and interdisciplinary applications. |
A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Empathy recognition and empathetic response generation tasks are well-established research directions, but there is little clarity on what empathy is and how it is being operationalized. |
| Approach: | They argue that current directions will benefit from a clear conceptualization that includes operationalizing cognitive empathy components. |
| Outcome: | The proposed framework will help to define and operationalize empathy in natural language processing. |