| Challenge: | citation networks are used to study scholarly articles' semantic distances and their referencing patterns. |
| Approach: | They propose to analyze the semantic distance of scholarly articles in a citation network to uncover patterns that reflect scientific impact. |
| Outcome: | The proposed method combines semantic distance and content similarity to uncover scientific impact of articles in two different types of publications. |
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| Challenge: | Scientific, engineering, and technological (SET) innovations drive many positive advances in our modern economy, society, and life. |
| Approach: | They propose a new metric that uses the content of the paper as a source of distant-supervision to quantify how much the cited-node informs the citing-n node. |
| Outcome: | The proposed method achieves up to 103% improvement over the second-best method. |
Beyond Citations: Corpus-based Methods for Detecting the Impact of Research Outcomes on Society (2020.lrec-1)
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| Challenge: | Existing methods for assessing the impact of research are ineffective for identifying impact beyond academia and text-based indicators beyond those that capture attention. |
| Approach: | They propose a deductive and inductive approach to categorize research impact categories using a corpus-based approach . they use a combination of deductive methods and machine learning to infer impact categories from project reports. |
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In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis (2026.acl-long)
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| Challenge: | citation counts are a shallow view that fails to capture how a paper has influenced subsequent work. |
| Approach: | They propose a task to generate nuanced, expressive, and time-aware impact summaries . they analyze fine-grained confirmatory and correction citation intents to generate summary . |
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CitationIE: Leveraging the Citation Graph for Scientific Information Extraction (2021.acl-long)
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| Challenge: | Existing work on scientific information extraction (SciIE) considers extraction solely based on the content of an individual paper, without considering the paper’s place in the broader literature. |
| Approach: | They propose to automate the extraction of key information from scientific documents by leveraging a complementary source: the citation graph of referential links between citing and cited papers. |
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The Noisy Path from Source to Citation: Measuring How Scholars Engage with Past Research (2025.acl-long)
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| Challenge: | Academic citations are widely used for evaluating research and tracing knowledge flows. |
| Approach: | They propose a computational pipeline to quantify citation fidelity at the sentence level by identifying citations in citing papers and corresponding claims in cited papers. |
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SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Prediction (2026.findings-acl)
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| Challenge: | Prior work on scientific impact prediction has focused on citation counts and its variants, leaving limited evaluation of models’ capability to reason about other dimensions. |
| Approach: | They propose a large-scale, multi-dimensional benchmark for scientific impact prediction spanning 19 fields. |
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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 . |
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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. |
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Beyond Metadata: What Paper Authors Say About Corpora They Use (2021.findings-acl)
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| Challenge: | Currently, dataset retrieval relies almost exclusively on metadata provided by the publishers. |
| Approach: | They propose to use metadata to extract review statements from scientific publications . they argue that a crucial piece of information is missing to inform the examination of search results . |
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Enhancing Scientific Document Summarization with Research Community Perspective and Background Knowledge (2024.lrec-main)
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| Challenge: | Scientific paper summarization is the focus of recent research . prevailing summarizing methods involve selective extraction of content from abstract, introduction, and conclusion segments within the target articles. |
| Approach: | They propose a model that incorporates references and citations to capture the impact of the document on the research community. |
| Outcome: | The proposed model generates extractive and abstractive summaries in parallel and improves their performance when considering the standard metrics. |