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Continual Relation Extraction
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Compared with traditional relation extraction, CRE aims to help the model learn new relations while maintaining accurate classification of old ones.
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Few-shot Continual Relation Extraction via Open Information Extraction
Adaptive Prompting for Continual Relation Extraction: A Within-Task Variance Perspective
Preserving Generalization of Language models in Few-shot Continual Relation Extraction
A Continual Relation Extraction Approach for Knowledge Graph Completeness
DP-CRE: Continual Relation Extraction via Decoupled Contrastive Learning and Memory Structure Preservation
Rationale-Enhanced Language Models are Better Continual Relation Learners
Improving Continual Relation Extraction by Distinguishing Analogous Semantics
Enhancing Contrastive Learning with Noise-Guided Attack: Towards Continual Relation Extraction in the Wild
Enhancing Continual Relation Extraction via Classifier Decomposition
Learning Robust Representations for Continual Relation Extraction via Adversarial Class Augmentation
Improving Continual Relation Extraction through Prototypical Contrastive Learning
Less is More: Rethinking State-of-the-art Continual Relation Extraction Models with a Frustratingly Easy but Effective Approach
Consistent Representation Learning for Continual Relation Extraction
Curriculum-Meta Learning for Order-Robust Continual Relation Extraction
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