CEPTNER: Contrastive learning Enhanced Prototypical network for Two-stage few-shot Named Entity Recognition-Reference-Cited by-同舟云学术

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CEPTNER: Contrastive learning Enhanced Prototypical network for Two-stage few-shot Named Entity Recognition

Published:2024-07 Issue: Volume:295 Page:111730
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Zha Enze,Zeng Delong,Lin Man,Shen Ying^ORCID

Publisher

Elsevier BV

Reference61 articles.

1. Heterogeneous supervision for relation extraction: A representation learning approach;Liu,2017

2. Joint entity recognition and disambiguation;Luo,2015

3. End-to-end sequence labeling via bi-directional LSTM-CNNs-CRF;Ma,2016

4. Neural architectures for named entity recognition;Lample,2016

5. Named entity recognition with bidirectional LSTM-CNNs;Chiu;Trans. Assoc. Comput. Linguist.,2016

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Scrutinizing Label: Contrastive Learning on Label Semantics and Enriched Representation for Relation Extraction;Cognitive Computation;2024-08-22

2. RepEKShot: an evidential k-nearest neighbor classifier with repulsion loss for few-shot named entity recognition;The Journal of Supercomputing;2024-06-20

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