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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 41–50 of 63 papers

TitleStatusHype
LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition—0
Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text ReconstructionCode0
Robust Few-Shot Named Entity Recognition with Boundary Discrimination and Correlation PurificationCode0
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
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
Enhancing Few-shot NER with Prompt Ordering based Data Augmentation—0
VicunaNER: Zero/Few-shot Named Entity Recognition using Vicuna—0
Causal Interventions-based Few-Shot Named Entity Recognition—0
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