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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 11–20 of 38 papers

TitleStatusHype
Using Domain Knowledge for Low Resource Named Entity Recognition—0
InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERCode1
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition—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 Based on Multi-hop Dependency TriggerCode0
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction—0
Data Augmentation for Low-Resource Named Entity Recognition Using BacktranslationCode0
Constrained Labeled Data Generation for Low-Resource Named Entity Recognition—0
Improving Low-Resource Named Entity Recognition via Label-Aware Data Augmentation and Curriculum Denoising—0
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