Fine Tuning an AraT5 Transformer for Arabic Abstractive Summarization-Reference-Cited by-同舟云学术

Fine Tuning an AraT5 Transformer for Arabic Abstractive Summarization

Published:2022-12-04 Issue: Volume: Page:
ISSN:
Container-title:2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)
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Author:

Einieh Yasmin¹,Almansour Amal¹,Jamal Amani¹

Affiliation:

1. King Abdulaziz University,Faculty of Computing and Information Technology,Jeddah,Saudi Arabia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10008224/10008233/10008272.pdf?arnumber=10008272

Reference29 articles.

1. Abstractive text summarization using LSTM-CNN based deep learning

2. A deep reinforced model for abstractive summarization;paulus;ArXiv Preprint,2017

3. Improving the readability and saliency of abstractive text summarization using combination of deep neural networks equipped with auxiliary attention mechanism;aliakbarpour;The Journal of Supercomputing,2021

4. Neural Abstractive Text Summarization with Sequence-to-Sequence Models

5. What Have We Achieved on Text Summarization?

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