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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 26–38 of 38 papers

TitleStatusHype
Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition—0
Using Domain Knowledge 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
Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help?—0
Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy LabelsCode0
Massively Multilingual Transfer for NERCode0
Memorisation versus Generalisation in Pre-trained Language ModelsCode0
Data Augmentation for Low-Resource Named Entity Recognition Using BacktranslationCode0
Low-Resource Named Entity Recognition Based on Multi-hop Dependency TriggerCode0
Towards Robust Named Entity Recognition for Historic GermanCode0
Translation and Fusion Improves Zero-shot Cross-lingual Information ExtractionCode0
Zero-Resource Cross-Lingual Named Entity RecognitionCode0
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