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 51–100 of 106 papers

TitleStatusHype
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple ExtractionCode0
Extracting Polymer Nanocomposite Samples from Full-Length DocumentsCode0
FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation ExtractionCode0
Fine-tune Bert for DocRED with Two-step ProcessCode0
Global Context-enhanced Graph Convolutional Networks for Document-level Relation ExtractionCode0
HistRED: A Historical Document-Level Relation Extraction DatasetCode0
Improving Document-level Relation Extraction via Contextualizing Mention Representations and Weighting Mention PairsCode0
LLM with Relation Classifier for Document-Level Relation ExtractionCode0
Multi-view Inference for Relation Extraction with Uncertain KnowledgeCode0
On the Robustness of Document-Level Relation Extraction Models to Entity Name VariationsCode0
Rethinking the Role of LLMs for Document-level Relation Extraction: a Refiner with Task Distribution and Probability FusionCode0
Revisiting Document-Level Relation Extraction with Context-Guided Link PredictionCode0
SagDRE: Sequence-Aware Graph-Based Document-Level Relation Extraction with Adaptive Margin LossCode0
Towards Better Document-level Relation Extraction via Iterative InferenceCode0
Towards Integration of Discriminability and Robustness for Document-Level Relation ExtractionCode0
TPN: Transferable Proto-Learning Network towards Few-shot Document-Level Relation ExtractionCode0
Improving Document-level Relation Extraction via Context Guided Mention Integration and Inter-pair Reasoning—0
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning—0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction—0
Key Mention Pairs Guided Document-Level Relation Extraction—0
KnowRA: Knowledge Retrieval Augmented Method for Document-level Relation Extraction with Comprehensive Reasoning Abilities—0
EIDER: Evidence-enhanced Document-level Relation Extraction—0
The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction—0
Mention-centered Graph Neural Network for Document-level Relation Extraction—0
Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction—0
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
Show:102550
← PrevPage 2 of 3Next →
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