SOTAVerified

Document-level Relation Extraction

Document-level RE aim to identify the relations of various entity pairs expressed across multiple sentences.

Papers

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Showing 21–30 of 106 papers

TitleStatusHype
Extracting Polymer Nanocomposite Samples from Full-Length DocumentsCode0
Revisiting Document-Level Relation Extraction with Context-Guided Link PredictionCode0
Adaptive Hinge Balance Loss for Document-Level Relation ExtractionCode0
Semi-automatic Data Enhancement for Document-Level Relation Extraction with Distant Supervision from Large Language ModelsCode1
Anaphor Assisted Document-Level Relation ExtractionCode1
RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation ExtractionCode1
Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language ModelsCode1
PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming—0
Document-Level Relation Extraction with Relation Correlation EnhancementCode0
A Comprehensive Survey of Document-level Relation Extraction (2016-2023)—0
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All datasetsBc8DocRED-IEDWIERe-DocRED

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BioRex+DirectionalityEvaluation Macro F156.06—Unverified
#ModelMetricClaimedVerifiedStatus
1REXELRelation F160.1—Unverified
#ModelMetricClaimedVerifiedStatus
1VaeDiff-DocREF10.73—Unverified
#ModelMetricClaimedVerifiedStatus
1VaeDiff-DocREF10.79—Unverified