Citation Recommendation
23 papers with code • 10 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Citation Recommendation
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Datasets
Microsoft Academic Graph
S2ORC
OC
Most implemented papers
HybridCite: A Hybrid Model for Context-Aware Citation Recommendation
The process of recommending citations for citation contexts is called local citation recommendation and is the focus of this paper.
CDLM: Cross-Document Language Modeling
aviclu/cdlm
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Findings (EMNLP) 2021
We introduce a new pretraining approach geared for multi-document language modeling, incorporating two key ideas into the masked language modeling self-supervised objective.
Content-Based Citation Recommendation
allenai/citeomatic
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NAACL 2018
We present a content-based method for recommending citations in an academic paper draft.
hyperdoc2vec: Distributed Representations of Hypertext Documents
Hypertext documents, such as web pages and academic papers, are of great importance in delivering information in our daily life.
Cross-language Citation Recommendation via Hierarchical Representation Learning on Heterogeneous Graph
While the volume of scholarly publications has increased at a frenetic pace, accessing and consuming the useful candidate papers, in very large digital libraries, is becoming an essential and challenging task for scholars.
A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networks
TeamLab/bert-gcn-for-paper-citation
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Many researchers have utilized the text data called the context sentence, which surrounds the citation tag, and the metadata of the target paper to find the appropriate cited research.
Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels
We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation.
Citation Recommendation: Approaches and Datasets
In recent years, several approaches and evaluation data sets have been presented.
unarXive: A Large Scholarly Data Set with Publications' Full-Text, Annotated In-Text Citations, and Links to Metadata
The data set, which is made freely available for research purposes, not only can enhance the future evaluation of research paper-based and citation context-based approaches, but also serve as a basis for new ways to analyze in-text citations, as we show prototypically in this article.
Semantic Modelling of Citation Contexts for Context-aware Citation Recommendation
New research is being published at a rate, at which it is infeasible for many scholars to read and assess everything possibly relevant to their work.
