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 76–100 of 106 papers

TitleStatusHype
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
NC-DRE: Leveraging Non-entity Clue Information for Document-level Relation Extraction—0
A Densely Connected Criss-Cross Attention Network for Document-level Relation Extraction—0
CorefDRE: Document-level Relation Extraction with coreference resolution—0
Document-level Relation Extraction with Context Guided Mention Integration and Inter-pair Reasoning—0
An Empirical Study on Relation Extraction in the Biomedical Domain—0
Translating Embeddings in Document for Modeling Multi-relational Graphs—0
Improving Document-level Relation Extraction via Context Guided Mention Integration and Inter-pair Reasoning—0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction—0
SagDRE: Sequence-Aware Graph-Based Document-Level Relation Extraction with Adaptive Margin LossCode0
Seq2rel: A sequence-to-sequence-based approach for document-level relation extraction—0
Modular Self-Supervision for Document-Level Relation Extraction—0
Entity and Evidence Guided Document-Level Relation Extraction—0
EIDER: Evidence-enhanced Document-level Relation Extraction—0
Multi-view Inference for Relation Extraction with Uncertain KnowledgeCode0
Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey—0
Mention-centered Graph Neural Network for Document-level Relation Extraction—0
Coarse-to-Fine Entity Representations for Document-level Relation ExtractionCode0
Global Context-enhanced Graph Convolutional Networks for Document-level Relation ExtractionCode0
Graph Enhanced Dual Attention Network for Document-Level Relation Extraction—0
Document-level Relation Extraction with Dual-tier Heterogeneous Graph—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