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 41–50 of 106 papers

TitleStatusHype
Document-Level Relation Extraction via Pair-Aware and Entity-Enhanced Representation Learning—0
Building a Japanese Document-Level Relation Extraction Dataset Assisted by Cross-Lingual Transfer—0
Augmenting Document-level Relation Extraction with Efficient Multi-Supervision—0
Entity and Evidence Guided Document-Level Relation Extraction—0
A Masked Image Reconstruction Network for Document-level Relation Extraction—0
DiVA-DocRE: A Discriminative and Voice-Aware Paradigm for Document-Level Relation Extraction—0
HIN: Hierarchical Inference Network for Document-Level Relation Extraction—0
Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey—0
Entity and Evidence Guided Relation Extraction for DocRED—0
CorefDRE: Document-level Relation Extraction with coreference resolution—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