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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
VicunaNER: Zero/Few-shot Named Entity Recognition using Vicuna—0
Few-Shot Named Entity Recognition with Biaffine Span Representation—0
Few-shot Named Entity Recognition with Joint Token and Sentence Awareness—0
Template-free Prompt Tuning for Few-shot NER—0
Hybrid Multi-stage Decoding for Few-shot NER with Entity-aware Contrastive Learning—0
PromptNER: Prompting For Named Entity Recognition—0
KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP—0
SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition—0
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
Few-shot Named Entity Recognition via Superposition Concept DiscriminationCode0
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