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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 1–50 of 63 papers

TitleStatusHype
FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual FrameworkCode0
Few-Shot Domain Adaptation for Named-Entity Recognition via Joint Constrained k-Means and Subspace SelectionCode0
CLLMFS: A Contrastive Learning enhanced Large Language Model Framework for Few-Shot Named Entity Recognition—0
Fighting Against the Repetitive Training and Sample Dependency Problem in Few-shot Named Entity Recognition—0
llmNER: (Zero|Few)-Shot Named Entity Recognition, Exploiting the Power of Large Language Models—0
A Unified Label-Aware Contrastive Learning Framework for Few-Shot Named Entity Recognition—0
LLMs in Biomedicine: A study on clinical Named Entity RecognitionCode0
Hybrid Multi-stage Decoding for Few-shot NER with Entity-aware Contrastive Learning—0
Few-shot Named Entity Recognition via Superposition Concept DiscriminationCode0
A Model Ensemble Approach with LLM for Chinese Text ClassificationCode0
Large-Scale Label Interpretation Learning for Few-Shot Named Entity Recognition—0
Designing Informative Metrics for Few-Shot Example Selection—0
Decomposed Meta-Learning for Few-Shot Sequence LabelingCode0
NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated DataCode1
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
HEProto: A Hierarchical Enhancing ProtoNet based on Multi-Task Learning for Few-shot Named Entity RecognitionCode1
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NERCode1
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
A Prototypical Semantic Decoupling Method via Joint Contrastive Learning for Few-Shot Name Entity Recognition—0
Meta-Learning Triplet Network with Adaptive Margins for Few-Shot Named Entity RecognitionCode1
Type-Aware Decomposed Framework for Few-Shot Named Entity RecognitionCode1
Prompt-Based Metric Learning for Few-Shot NERCode1
Language Model Pre-Training with Sparse Latent TypingCode1
Robustness of Demonstration-based Learning Under Limited Data ScenarioCode0
SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition—0
SEE-Few: Seed, Expand and Entail for Few-shot Named Entity RecognitionCode1
PCBERT: Parent and Child BERT for Chinese Few-shot NERCode0
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity RecognitionCode1
FactMix: Using a Few Labeled In-domain Examples to Generalize to Cross-domain Named Entity RecognitionCode1
KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP—0
Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity RecognitionCode0
mGPT: Few-Shot Learners Go MultilingualCode2
Decomposed Meta-Learning for Few-Shot Named Entity RecognitionCode2
Few-shot Named Entity Recognition with Self-describing NetworksCode1
Label Semantics for Few Shot Named Entity RecognitionCode1
InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERCode1
QaNER: Prompting Question Answering Models for Few-shot Named Entity RecognitionCode1
Template-free Prompt Tuning for Few-shot NER—0
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