Papers Citation Intent Classification
“Citation Intent Classification” 태그가 달린 논문 18편 · 필터 해제
A Large-Scale Dataset and Citation Intent Classification in Turkish with LLMs
Understanding the qualitative intent of citations is essential for a comprehensive assessment of academic research, a task that poses unique challenges for agglutinative languages like Turkish. This paper introduces a sy…
Citation Intent ClassificationLeveraging GANs for citation intent classification and its impact on citation network analysis
Citations play a fundamental role in the scientific ecosystem, serving as a foundation for tracking the flow of knowledge, acknowledging prior work, and assessing scholarly influence. In scientometrics, they are also cen…
Citation Intent Classificationintent-classificationIntent ClassificationWhy do you cite? An investigation on citation intents and decision-making classification processes
Identifying the reason for which an author cites another work is essential to understand the nature of scientific contributions and to assess their impact. Citations are one of the pillars of scholarly communication and …
Citation Intent ClassificationDecision Makingintent-classificationIntent ClassificationCitePrompt: Using Prompts to Identify Citation Intent in Scientific Papers
Citations in scientific papers not only help us trace the intellectual lineage but also are a useful indicator of the scientific significance of the work. Citation intents prove beneficial as they specify the role of the…
ARCCitation Intent Classificationintent-classificationIntent Classification+1VarMAE: Pre-training of Variational Masked Autoencoder for Domain-adaptive Language Understanding
Pre-trained language models have achieved promising performance on general benchmarks, but underperform when migrated to a specific domain. Recent works perform pre-training from scratch or continual pre-training on doma…
Citation Intent ClassificationLanguage ModelingLanguage ModellingTowards Better Citation Intent Classification
Accurate classification of citation intents in a scientific article provides deeper contextual understanding of and better quantifies the contributions of cited articles. This improves scientific literature platform capa…
ArticlesCitation Intent ClassificationClassificationData Augmentation+3Cross-Lingual Citations in English Papers: A Large-Scale Analysis of Prevalence, Usage, and Impact
Citation information in scholarly data is an important source of insight into the reception of publications and the scholarly discourse. Outcomes of citation analyses and the applicability of citation based machine learn…
Citation Intent ClassificationCross-Lingual Entity LinkingData VisualizationGenerative Adversarial Networks based on Mixed-Attentions for Citation Intent Classification in Scientific Publications
We propose the mixed-attention-based Generative Adversarial Network (named maGAN), and apply it for citation intent classification in scientific publication. We select domain-specific training data, propose a mixed-atten…
Citation Intent ClassificationClassificationGenerative Adversarial Networkintent-classification+4SciWING– A Software Toolkit for Scientific Document Processing
We introduce SciWING, an open-source soft-ware toolkit which provides access to state-of-the-art pre-trained models for scientific document processing (SDP) tasks, such as citation string parsing, logical structure recov…
Citation Intent Classificationintent-classificationIntent ClassificationTransfer LearningImpactCite: An XLNet-based method for Citation Impact Analysis
Citations play a vital role in understanding the impact of scientific literature. Generally, citations are analyzed quantitatively whereas qualitative analysis of citations can reveal deeper insights into the impact of a…
Citation Intent ClassificationClassificationGeneral Classificationintent-classification+3Don't Stop Pretraining: Adapt Language Models to Domains and Tasks
Language models pretrained on text from a wide variety of sources form the foundation of today's NLP. In light of the success of these broad-coverage models, we investigate whether it is still helpful to tailor a pretrai…
Citation Intent ClassificationStructural Scaffolds for Citation Intent Classification in Scientific Publications
Identifying the intent of a citation in scientific papers (e.g., background information, use of methods, comparing results) is critical for machine reading of individual publications and automated analysis of the scienti…
ARCCitation Intent ClassificationClassificationGeneral Classification+4SciBERT: A Pretrained Language Model for Scientific Text
Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive. We release SciBERT, a pretrained language model based on BERT (Devlin et al., 2018) to address the lack of high-qu…
Citation Intent ClassificationDependency ParsingGeneral ClassificationLanguage Modeling+8BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bid…
Citation Intent ClassificationCommon Sense ReasoningConversational Response SelectionCoreference Resolution+17Deep contextualized word representations
We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i.e., to m…
Citation Intent ClassificationConversational Response SelectionCoreference ResolutionLanguage Modeling+7