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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
How far is Language Model from 100% Few-shot Named Entity Recognition in Medical DomainCode1
TKDP: Threefold Knowledge-enriched Deep Prompt Tuning for Few-shot Named Entity RecognitionCode0
ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER—0
PromptNER: Prompting For Named Entity Recognition—0
PromptNER: A Prompting Method for Few-shot Named Entity Recognition via k Nearest Neighbor SearchCode1
Enhancing Few-shot NER with Prompt Ordering based Data Augmentation—0
Learning In-context Learning for Named Entity RecognitionCode1
From Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot ContextsCode1
VicunaNER: Zero/Few-shot Named Entity Recognition using Vicuna—0
Causal Interventions-based Few-Shot Named Entity Recognition—0
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