Citation Recommendation
26 papers with code • 10 benchmarks • 9 datasets
Datasets
Most implemented papers
Multilevel Text Alignment with Cross-Document Attention
Text alignment finds application in tasks such as citation recommendation and plagiarism detection.
Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input Modalities
In conclusion, it is crucial to consider the semantics of the item co-occurrence for the choice of an appropriate recommendation model and carefully decide which metadata to exploit.
Citation Recommendation for Research Papers via Knowledge Graphs
Citation recommendation for research papers is a valuable task that can help researchers improve the quality of their work by suggesting relevant related work.
Context-Aware Legal Citation Recommendation using Deep Learning
Lawyers and judges spend a large amount of time researching the proper legal authority to cite while drafting decisions.
ACM-CR: A Manually Annotated Test Collection for Citation Recommendation
Our test collection and code to replicate experiments are available at https://github. com/boudinfl/acm-cr
Local Citation Recommendation with Hierarchical-Attention Text Encoder and SciBERT-based Reranking
The goal of local citation recommendation is to recommend a missing reference from the local citation context and optionally also from the global context.
Improving Wikipedia Verifiability with AI
Hence, maintaining and improving the quality of Wikipedia references is an important challenge and there is a pressing need for better tools to assist humans in this effort.
Large-scale Evaluation of Transformer-based Article Encoders on the Task of Citation Recommendation
As a remedy for the limitations of the existing benchmarks, we propose a new benchmark dataset for evaluating scientific article representations: Multi-Domain Citation Recommendation dataset (MDCR), which covers different scientific fields and contains challenging candidate pools.
Legal Case Document Similarity: You Need Both Network and Text
Our experiments establish that our proposed network-based methods significantly improve the correlation with domain experts' opinion when compared to the existing methods for network-based legal document similarity.
unarXive 2022: All arXiv Publications Pre-Processed for NLP, Including Structured Full-Text and Citation Network
Large-scale data sets on scholarly publications are the basis for a variety of bibliometric analyses and natural language processing (NLP) applications.