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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 21–30 of 38 papers

TitleStatusHype
Low-Resource Named Entity Recognition with Cross-Lingual, Character-Level Neural Conditional Random Fields—0
Prompt-based Text Entailment for Low-Resource Named Entity Recognition—0
RoPDA: Robust Prompt-based Data Augmentation for Low-Resource Named Entity Recognition—0
SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models—0
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models—0
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
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