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 71–80 of 106 papers

TitleStatusHype
Towards Better Document-level Relation Extraction via Iterative InferenceCode0
Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modeling—0
ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction—0
Key Mention Pairs Guided Document-Level Relation Extraction—0
Document-Level Relation Extraction via Pair-Aware and Entity-Enhanced Representation Learning—0
Improving Distantly Supervised Document-Level Relation Extraction Through Natural Language Inference—0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple ExtractionCode0
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning—0
Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction—0
A Masked Image Reconstruction Network for Document-level Relation Extraction—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