Class conditioned text generation with style attention mechanism for embracing diversity-Reference-Cited by-同舟云学术

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Class conditioned text generation with style attention mechanism for embracing diversity

Published:2024-09 Issue: Volume:163 Page:111893
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Kwon Naae,Yoo Yuenkyung,Lee Byunghan^ORCID

Funder

Ministry of Science, ICT and Future Planning

Korea Ministry of Science and ICT

National Research Foundation of Korea

Information Technology Research Centre

Institute for Information and Communications Technology Promotion

Publisher

Elsevier BV

Reference44 articles.

1. Attention is all you need;Vaswani;Advances in neural information processing systems,2017

2. Improving language understanding by generative pre-training;Radford,2018

3. Deep residual learning for image recognition;He,2016

4. Character Recognition Techniques and approaches: a literature review;Mohammed;Mesopotamian J. Comput. Sci.,2021

5. Dialogpt: Large-scale generative pre-training for conversational response generation;Zhang,2019

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