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 11–20 of 106 papers

TitleStatusHype
Consistent Document-Level Relation Extraction via CounterfactualsCode0
EVA-Score: Evaluating Abstractive Long-form Summarization on Informativeness through Extraction and Validation—0
Augmenting Document-level Relation Extraction with Efficient Multi-Supervision—0
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels—0
On the Robustness of Document-Level Relation Extraction Models to Entity Name VariationsCode0
TTM-RE: Memory-Augmented Document-Level Relation ExtractionCode1
Building a Japanese Document-Level Relation Extraction Dataset Assisted by Cross-Lingual Transfer—0
REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity LinkingCode1
AutoRE: Document-Level Relation Extraction with Large Language ModelsCode2
FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation ExtractionCode0
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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