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 31–40 of 106 papers

TitleStatusHype
Double Graph Based Reasoning for Document-level Relation ExtractionCode1
Document-Level Relation Extraction with Sentences Importance Estimation and FocusingCode1
Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge DistillationCode1
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation ExtractionCode1
An End-to-end Model for Entity-level Relation Extraction using Multi-instance LearningCode1
DREEAM: Guiding Attention with Evidence for Improving Document-Level Relation ExtractionCode1
Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language ModelsCode1
Does Recommend-Revise Produce Reliable Annotations? An Analysis on Missing Instances in DocREDCode1
DORE: Document Ordered Relation Extraction based on Generative FrameworkCode1
Uncertainty Guided Label Denoising for Document-level Distant Relation ExtractionCode1
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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