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 91–100 of 106 papers

TitleStatusHype
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