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 51–60 of 106 papers

TitleStatusHype
EVA-Score: Evaluating Abstractive Long-form Summarization on Informativeness through Extraction and Validation—0
Augmenting Document-level Relation Extraction with Efficient Multi-Supervision—0
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels—0
On the Robustness of Document-Level Relation Extraction Models to Entity Name VariationsCode0
Building a Japanese Document-Level Relation Extraction Dataset Assisted by Cross-Lingual Transfer—0
FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation ExtractionCode0
Extracting Polymer Nanocomposite Samples from Full-Length DocumentsCode0
Revisiting Document-Level Relation Extraction with Context-Guided Link PredictionCode0
Adaptive Hinge Balance Loss for Document-Level Relation ExtractionCode0
PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming—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