Mix of Experts Language Model for Named Entity Recognition-Reference-Cited by-同舟云学术

Mix of Experts Language Model for Named Entity Recognition

Published:2024-05-10 Issue: Volume:33 Page:502-506
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Container-title:2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE)
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Author:

Chen Xinwei¹,Li Kun²,Song Tianyou³,Guo Jiangjian⁴

Affiliation:

1. University of Illinois at Urbana Champaign,Department of Electronical and Computer Engineering,Urbana,IL,USA

2. University of Illinois at Urbana Champaign,Department of Computer Science,Urbana,IL,USA

3. Columbia University,Department of Computer Science,New York,USA

4. University of California San Diego,Department of Computer Science and Engineering,La Jolla,US

Publisher

IEEE

Link

Reference21 articles.

1. Bert: Pre-training of deep bidirectional transformers for language understanding;Devlin;arXiv preprint,2018

2. Few-shot name entity recognition on stackoverflow;Chen;arXiv preprint,2024

3. Conditional random fields: Probabilistic models for segmenting and labeling sequence data;Lafferty

4. Deception detection from linguistic and physiological data streams using bimodal convolutional neural networks;Li;arXiv preprint,2023

5. Language models are few-shot learners;Brown;Advances in neural information processing systems,2020

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