SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 63 papers

TitleStatusHype
Probing Pre-trained Auto-regressive Language Models for Named Entity Typing and RecognitionCode0
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
Learning from Miscellaneous Other-Class Words for Few-shot Named Entity RecognitionCode0
Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text ReconstructionCode0
Robustness of Demonstration-based Learning Under Limited Data ScenarioCode0
Few-Shot Domain Adaptation for Named-Entity Recognition via Joint Constrained k-Means and Subspace SelectionCode0
Few-shot Named Entity Recognition via Superposition Concept DiscriminationCode0
TKDP: Threefold Knowledge-enriched Deep Prompt Tuning for Few-shot Named Entity RecognitionCode0
A Model Ensemble Approach with LLM for Chinese Text ClassificationCode0
PCBERT: Parent and Child BERT for Chinese Few-shot NERCode0
Show:102550
← PrevPage 4 of 7Next →

No leaderboard results yet.