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 26–50 of 106 papers

TitleStatusHype
RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation ExtractionCode1
Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language ModelsCode1
PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming—0
Document-Level Relation Extraction with Relation Correlation EnhancementCode0
A Comprehensive Survey of Document-level Relation Extraction (2016-2023)—0
PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score CalibrationCode1
GADePo: Graph-Assisted Declarative Pooling Transformers for Document-Level Relation Extraction—0
HistRED: A Historical Document-Level Relation Extraction DatasetCode0
A Positive-Unlabeled Metric Learning Framework for Document-Level Relation Extraction with Incomplete LabelingCode0
Did the Models Understand Documents? Benchmarking Models for Language Understanding in Document-Level Relation ExtractionCode0
Rethinking Document-Level Relation Extraction: A Reality Check—0
Uncertainty Guided Label Denoising for Document-level Distant Relation ExtractionCode1
Towards Integration of Discriminability and Robustness for Document-Level Relation ExtractionCode0
Document-level Relation Extraction with Cross-sentence Reasoning GraphCode0
DREEAM: Guiding Attention with Evidence for Improving Document-Level Relation ExtractionCode1
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
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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