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 76–100 of 106 papers

TitleStatusHype
Modular Self-Supervision for Document-Level Relation Extraction—0
Document-level Relation Extraction with Dual-tier Heterogeneous Graph—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
Document-level Relation Extraction with Context Guided Mention Integration and Inter-pair Reasoning—0
Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modeling—0
A Densely Connected Criss-Cross Attention Network for Document-level Relation Extraction—0
Document-Level Relation Extraction via Pair-Aware and Entity-Enhanced Representation Learning—0
PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming—0
Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey—0
CorefDRE: Document-level Relation Extraction with coreference resolution—0
ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction—0
Rethinking Document-Level Relation Extraction: A Reality Check—0
A Comprehensive Survey of Document-level Relation Extraction (2016-2023)—0
COMM:Concentrated Margin Maximization for Robust Document-Level Relation Extraction—0
DiVA-DocRE: A Discriminative and Voice-Aware Paradigm for Document-Level Relation Extraction—0
EVA-Score: Evaluating Abstractive Long-form Summarization on Informativeness through Extraction and Validation—0
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels—0
Translating Embeddings in Document for Modeling Multi-relational Graphs—0
Entity and Evidence Guided Relation Extraction for DocRED—0
Building a Japanese Document-Level Relation Extraction Dataset Assisted by Cross-Lingual Transfer—0
GADePo: Graph-Assisted Declarative Pooling Transformers for Document-Level Relation Extraction—0
GEGA: Graph Convolutional Networks and Evidence Retrieval Guided Attention for Enhanced Document-level Relation Extraction—0
Augmenting Document-level Relation Extraction with Efficient Multi-Supervision—0
Entity and Evidence Guided 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