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LinkBERT: Pretraining Language Models with Document Links

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)(2022)10.18653/v1/2022.acl-long.551Source: DataRank Database

LinkBERT: Pretraining Language Models with Document Links is a research paper published in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022). On theSindex it has a DataRank of 0. It has been cited 303 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access303 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (6 grants)Impact (FWCI 45.88)OA: hybridTopics (23)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (3)

Jure Leskovec ORCID,Percy Liang ORCID,Michihiro Yasunaga ORCID

Live enrichment

PubMed:30945415 OpenAlex:https://openalex.org/W4221153690

National Science Foundation

Grant: 1552635

CAREER: Interactive Training of Semantic Parsers via Paraphrasing

National Institutes of Health

Grant: 1R56LM013365-01A1

Machine Learning Clinical Order Recommendations for Specialty Consultation Care

National Science Foundation

Grant: 1918940

Expeditions: Collaborative Research: Global Pervasive Computational Epidemiology

National Science Foundation

Grant: 1934578

The Stanford Data Science Collaboratory

National Science Foundation

Grant: 2030477

RAPID: Collaborative Research: Computational Drug Repurposing for COVID-19

National Science Foundation

Grant: 1835598

Collaborative Research: Framework: Software: CINES: A Scalable Cyberinfrastructure for Sustained Innovation in Network Engineering and Science

FWCI

45.88

Citation Percentile

1.0%

Citation Trend

2022

2023

2024

2025

2026

hybridLicense: cc-by

conferencehttps://aclanthology.org/2022.acl-long.551.pdf

publisherhttps://aclanthology.org/2022.acl-long.551.pdf

conferencehttps://doi.org/10.18653/v1/2022.acl-long.551

https://dx.doi.org/10.48550/arxiv.2203.15827

http://arxiv.org/abs/2203.15827

Fields of Study

Topic ModelingNatural Language Processing TechniquesBiomedical Text Mining and Ontologies0202 electrical engineering, electronic engineering, information engineering02 engineering and technology01 natural sciences0105 earth and related environmental sciences

Keywords

Computer scienceHyperlinkLanguage modelNatural language processingArtificial intelligenceInformation retrievalContext (archaeology)GraphDomain (mathematical analysis)World Wide WebWeb pageFOS: Computer and information sciencesComputer Science - Machine LearningComputer Science - Computation and LanguageComputation and Language (cs.CL)Machine Learning (cs.LG)

Sustainable Development Goals

SDG 0: Quality Education

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