Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization

Ziqiang Cao, Wenjie Li, Sujian Li, Furu Wei
2018 Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
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 templateaware summary generation
more » ... 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.
doi:10.18653/v1/p18-1015 dblp:conf/acl/LiWLC18 fatcat:ak6jzmyonzgipjl7ksjrj7dxua