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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
GoLLIE: Annotation Guidelines improve Zero-Shot Information-ExtractionCode2
ANEA: Distant Supervision for Low-Resource Named Entity RecognitionCode1
InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERCode1
SEE-Few: Seed, Expand and Entail for Few-shot Named Entity RecognitionCode1
Soft Gazetteers for Low-Resource Named Entity RecognitionCode1
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity RecognitionCode1
A Robust and Domain-Adaptive Approach for Low-Resource Named Entity RecognitionCode1
AutoTriggER: Named Entity Recognition with Auxiliary Trigger Extraction—0
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction—0
AUC Maximization for Low-Resource Named Entity Recognition—0
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