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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 1–10 of 38 papers

TitleStatusHype
Low-Resource Named Entity Recognition with Cross-Lingual, Character-Level Neural Conditional Random Fields—0
Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help?—0
GoLLIE: Annotation Guidelines improve Zero-Shot Information-ExtractionCode2
RoPDA: Robust Prompt-based Data Augmentation for Low-Resource Named Entity Recognition—0
Translation and Fusion Improves Zero-shot Cross-lingual Information ExtractionCode0
AUC Maximization for Low-Resource Named Entity Recognition—0
Prompt-based Text Entailment for Low-Resource Named Entity Recognition—0
SEE-Few: Seed, Expand and Entail for Few-shot Named Entity RecognitionCode1
SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models—0
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity RecognitionCode1
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