Exploring the Impact of Syntactic Structure Information on Unknown Entity Recognition in Transformer-based Natural Language Understanding-Reference-Cited by-同舟云学术

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Exploring the Impact of Syntactic Structure Information on Unknown Entity Recognition in Transformer-based Natural Language Understanding

Published:2023-07-08 Issue: Volume: Page:
ISSN:
Container-title:2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)
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Author:

Yang Rui¹,Javar Farnoosh¹,Wakabayashi Kei¹,Takeuchi Johane²

Affiliation:

1. University of Tsukuba,Ibaraki,Japan

2. Honda Research Institute Japan Co., Ltd.,Saitama,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10371369/10371409/10371529.pdf?arnumber=10371529

Reference27 articles.

1. Diet: Lightweight language understanding for dialogue systems;Bunk;arXiv:2004.09936 [cs.CL],2020

2. Graph convolutional networks for named entity recognition;Cetoli,2018

3. Graph convolutional networks for named entity recognition;Cetoli;arXiv:1709.10053 [cs.CL],2017

4. Named Entity Recognition with Bidirectional LSTM-CNNs

5. Electra: Pre-training text encoders as discriminators rather than generators;Clark,2020

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