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        <title>Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization</title>
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    <abstract>Most previous seq2seq summarization systems purely depend on the source text to generate summaries, which tends to work unstably. Inspired by the traditional template-based summarization approaches, this paper proposes to use existing summaries as soft templates to guide the seq2seq model. To this end, we use a popular IR platform to Retrieve proper summaries as candidate templates. Then, we extend the seq2seq framework to jointly conduct template Reranking and template-aware summary generation (Rewriting). Experiments show that, in terms of informativeness, our model significantly outperforms the state-of-the-art methods, and even soft templates themselves demonstrate high competitiveness. In addition, the import of high-quality external summaries improves the stability and readability of generated summaries.</abstract>
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%0 Conference Proceedings
%T Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization
%A Cao, Ziqiang
%A Li, Wenjie
%A Li, Sujian
%A Wei, Furu
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F cao-etal-2018-retrieve
%X Most previous seq2seq summarization systems purely depend on the source text to generate summaries, which tends to work unstably. Inspired by the traditional template-based summarization approaches, this paper proposes to use existing summaries as soft templates to guide the seq2seq model. To this end, we use a popular IR platform to Retrieve proper summaries as candidate templates. Then, we extend the seq2seq framework to jointly conduct template Reranking and template-aware summary generation (Rewriting). Experiments show that, in terms of informativeness, our model significantly outperforms the state-of-the-art methods, and even soft templates themselves demonstrate high competitiveness. In addition, the import of high-quality external summaries improves the stability and readability of generated summaries.
%R 10.18653/v1/P18-1015
%U https://aclanthology.org/P18-1015
%U https://doi.org/10.18653/v1/P18-1015
%P 152-161

Markdown (Informal)

[Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization](https://aclanthology.org/P18-1015) (Cao et al., ACL 2018)

• Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization (Cao et al., ACL 2018)

ACL

• Ziqiang Cao, Wenjie Li, Sujian Li, and Furu Wei. 2018. Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 152–161, Melbourne, Australia. Association for Computational Linguistics.