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Few-shot NER

Few-Shot Named Entity Recognition (NER) is the task of recognising a 'named entity' like a person, organization, time and so on in a piece of text e.g. "Alan Mathison [person] visited the Turing Institute [organization] in June [time].

Papers

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Showing 21–30 of 63 papers

TitleStatusHype
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive LearningCode1
Label Semantics for Few Shot Named Entity RecognitionCode1
From Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot ContextsCode1
Few-shot Named Entity Recognition with Self-describing NetworksCode1
Meta-Learning Triplet Network with Adaptive Margins for Few-Shot Named Entity RecognitionCode1
Simple Questions Generate Named Entity Recognition DatasetsCode1
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity RecognitionCode1
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity RecognitionCode0
Decomposed Meta-Learning for Few-Shot Sequence LabelingCode0
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