SOTAVerified

Document-level Relation Extraction

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 106 papers

TitleStatusHype
Document-level Relation Extraction with Relation CorrelationsCode0
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
DORE: Document Ordered Relation Extraction based on Generative FrameworkCode1
A Unified Positive-Unlabeled Learning Framework for Document-Level Relation Extraction with Different Levels of LabelingCode1
ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction—0
Document-Level Relation Extraction via Pair-Aware and Entity-Enhanced Representation Learning—0
Key Mention Pairs Guided Document-Level Relation Extraction—0
Enhancing Document-level Relation Extraction by Entity Knowledge InjectionCode1
Improving Distantly Supervised Document-Level Relation Extraction Through Natural Language Inference—0
Show:102550
← PrevPage 5 of 11Next →
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