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Low Resource Named Entity Recognition

Low resource named entity recognition is the task of using data and models available for one language for which ample such resources are available (e.g., English) to solve named entity recognition tasks in another, commonly more low-resource, language.

Papers

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Showing 1–25 of 38 papers

TitleStatusHype
GoLLIE: Annotation Guidelines improve Zero-Shot Information-ExtractionCode2
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity RecognitionCode1
ANEA: Distant Supervision for Low-Resource Named Entity RecognitionCode1
A Robust and Domain-Adaptive Approach for Low-Resource Named Entity RecognitionCode1
Soft Gazetteers for Low-Resource Named Entity RecognitionCode1
SEE-Few: Seed, Expand and Entail for Few-shot Named Entity RecognitionCode1
InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERCode1
Zero-Resource Cross-Lingual Named Entity RecognitionCode0
Memorisation versus Generalisation in Pre-trained Language ModelsCode0
Translation and Fusion Improves Zero-shot Cross-lingual Information ExtractionCode0
Data Augmentation for Low-Resource Named Entity Recognition Using BacktranslationCode0
Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy LabelsCode0
Low-Resource Named Entity Recognition Based on Multi-hop Dependency TriggerCode0
Massively Multilingual Transfer for NERCode0
Towards Robust Named Entity Recognition for Historic GermanCode0
DATNet: Dual Adversarial Transfer for Low-resource Named Entity Recognition—0
Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and Yorùbá—0
Dual Adversarial Neural Transfer for Low-Resource Named Entity Recognition—0
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models—0
Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition—0
Improving Low-Resource Named Entity Recognition using Joint Sentence and Token Labeling—0
Improving Low-Resource Named Entity Recognition via Label-Aware Data Augmentation and Curriculum Denoising—0
AutoTriggER: Named Entity Recognition with Auxiliary Trigger Extraction—0
Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition—0
Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help?—0
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