VAE-PGN based Abstractive Model in Multi-stage Architecture for Text Summarization

Hyungtak Choi, Lohith Ravuru, Tomasz Dryjański, Sunghan Rye, Donghyun Lee, Hojung Lee, Inchul Hwang


Abstract
This paper describes our submission to the TL;DR challenge. Neural abstractive summarization models have been successful in generating fluent and consistent summaries with advancements like the copy (Pointer-generator) and coverage mechanisms. However, these models suffer from their extractive nature as they learn to copy words from the source text. In this paper, we propose a novel abstractive model based on Variational Autoencoder (VAE) to address this issue. We also propose a Unified Summarization Framework for the generation of summaries. Our model eliminates non-critical information at a sentence-level with an extractive summarization module and generates the summary word by word using an abstractive summarization module. To implement our framework, we combine submodules with state-of-the-art techniques including Pointer-Generator Network (PGN) and BERT while also using our new VAE-PGN abstractive model. We evaluate our model on the benchmark Reddit corpus as part of the TL;DR challenge and show that our model outperforms the baseline in ROUGE score while generating diverse summaries.
Anthology ID:
W19-8664
Volume:
Proceedings of the 12th International Conference on Natural Language Generation
Month:
October–November
Year:
2019
Address:
Tokyo, Japan
Editors:
Kees van Deemter, Chenghua Lin, Hiroya Takamura
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
510–515
Language:
URL:
https://aclanthology.org/W19-8664
DOI:
10.18653/v1/W19-8664
Bibkey:
Cite (ACL):
Hyungtak Choi, Lohith Ravuru, Tomasz Dryjański, Sunghan Rye, Donghyun Lee, Hojung Lee, and Inchul Hwang. 2019. VAE-PGN based Abstractive Model in Multi-stage Architecture for Text Summarization. In Proceedings of the 12th International Conference on Natural Language Generation, pages 510–515, Tokyo, Japan. Association for Computational Linguistics.
Cite (Informal):
VAE-PGN based Abstractive Model in Multi-stage Architecture for Text Summarization (Choi et al., INLG 2019)
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PDF:
https://aclanthology.org/W19-8664.pdf