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 51–100 of 106 papers

TitleStatusHype
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple ExtractionCode0
Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation ExtractionCode1
Revisiting DocRED -- Addressing the False Negative Problem in Relation ExtractionCode1
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
Few-Shot Document-Level Relation ExtractionCode1
None Class Ranking Loss for Document-Level Relation ExtractionCode1
Document-Level Relation Extraction with Sentences Importance Estimation and FocusingCode1
A Masked Image Reconstruction Network for Document-level Relation Extraction—0
Does Recommend-Revise Produce Reliable Annotations? An Analysis on Missing Instances in DocREDCode1
A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and GenesCode1
A sequence-to-sequence approach for document-level relation extractionCode1
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
Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge DistillationCode1
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
Seq2rel: A sequence-to-sequence-based approach for document-level relation extraction—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
Learning Logic Rules for Document-level Relation ExtractionCode1
SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation ExtractionCode1
Modular Self-Supervision for Document-Level Relation Extraction—0
Entity and Evidence Guided Document-Level Relation Extraction—0
MRN: A Locally and Globally Mention-Based Reasoning Network for Document-Level Relation ExtractionCode1
EIDER: Evidence-enhanced Document-level Relation Extraction—0
Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage FusionCode1
Document-level Relation Extraction as Semantic SegmentationCode1
Discriminative Reasoning for Document-level Relation ExtractionCode1
Three Sentences Are All You Need: Local Path Enhanced Document Relation ExtractionCode1
SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation ExtractionCode1
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
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation ExtractionCode1
An End-to-end Model for Entity-level Relation Extraction using Multi-instance LearningCode1
Document-Level Relation Extraction with ReconstructionCode1
Coarse-to-Fine Entity Representations for Document-level Relation ExtractionCode0
Global Context-enhanced Graph Convolutional Networks for Document-level Relation ExtractionCode0
Document-level Relation Extraction with Dual-tier Heterogeneous Graph—0
Graph Enhanced Dual Attention Network for Document-Level Relation Extraction—0
Denoising Relation Extraction from Document-level Distant SupervisionCode1
The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction—0
Document-Level Relation Extraction with Adaptive Thresholding and Localized Context PoolingCode1
Double Graph Based Reasoning for Document-level Relation ExtractionCode1
Global-to-Local Neural Networks for Document-Level Relation ExtractionCode1
Entity and Evidence Guided Relation Extraction for DocRED—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