SOTAVerified

Document-level Relation Extraction

Document-level RE aim to identify the relations of various entity pairs expressed across multiple sentences.

Papers

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Showing 61–70 of 106 papers

TitleStatusHype
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
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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