SOTAVerified

Continual Relation Extraction

Compared with traditional relation extraction, CRE aims to help the model learn new relations while maintaining accurate classification of old ones.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 16 papers

TitleStatusHype
Towards Rehearsal-Free Continual Relation Extraction: Capturing Within-Task Variance with Adaptive PromptingCode0
Few-shot Continual Relation Extraction via Open Information Extraction—0
Adaptive Prompting for Continual Relation Extraction: A Within-Task Variance Perspective—0
Preserving Generalization of Language models in Few-shot Continual Relation ExtractionCode0
A Continual Relation Extraction Approach for Knowledge Graph Completeness—0
DP-CRE: Continual Relation Extraction via Decoupled Contrastive Learning and Memory Structure Preservation—0
Rationale-Enhanced Language Models are Better Continual Relation LearnersCode1
Enhancing Contrastive Learning with Noise-Guided Attack: Towards Continual Relation Extraction in the Wild—0
Improving Continual Relation Extraction by Distinguishing Analogous SemanticsCode1
Enhancing Continual Relation Extraction via Classifier DecompositionCode1
Show:102550
← PrevPage 1 of 2Next →

No leaderboard results yet.