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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
Improving Low-Resource Named Entity Recognition using Joint Sentence and Token Labeling—0
Building Low-Resource NER Models Using Non-Speaker Annotation—0
Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and Yorùbá—0
Zero-Resource Cross-Lingual Named Entity RecognitionCode0
Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy LabelsCode0
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models—0
Dual Adversarial Neural Transfer for Low-Resource Named Entity Recognition—0
Towards Robust Named Entity Recognition for Historic GermanCode0
Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition—0
DATNet: Dual Adversarial Transfer for Low-resource Named Entity Recognition—0
Massively Multilingual Transfer for NERCode0
Low-resource named entity recognition via multi-source projection: Not quite there yet?—0
Bayesian Modeling of Lexical Resources for Low-Resource Settings—0
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