@inproceedings{suzuki-nagata-2017-cutting,
    title = "Cutting-off Redundant Repeating Generations for Neural Abstractive Summarization",
    author = "Suzuki, Jun  and
      Nagata, Masaaki",
    editor = "Lapata, Mirella  and
      Blunsom, Phil  and
      Koller, Alexander",
    booktitle = "Proceedings of the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics: Volume 2, Short Papers",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/E17-2047/",
    pages = "291--297",
    abstract = "This paper tackles the reduction of redundant repeating generation that is often observed in RNN-based encoder-decoder models. Our basic idea is to jointly estimate the upper-bound frequency of each target vocabulary in the encoder and control the output words based on the estimation in the decoder. Our method shows significant improvement over a strong RNN-based encoder-decoder baseline and achieved its best results on an abstractive summarization benchmark."
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%0 Conference Proceedings
%T Cutting-off Redundant Repeating Generations for Neural Abstractive Summarization
%A Suzuki, Jun
%A Nagata, Masaaki
%Y Lapata, Mirella
%Y Blunsom, Phil
%Y Koller, Alexander
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F suzuki-nagata-2017-cutting
%X This paper tackles the reduction of redundant repeating generation that is often observed in RNN-based encoder-decoder models. Our basic idea is to jointly estimate the upper-bound frequency of each target vocabulary in the encoder and control the output words based on the estimation in the decoder. Our method shows significant improvement over a strong RNN-based encoder-decoder baseline and achieved its best results on an abstractive summarization benchmark.
%U https://aclanthology.org/E17-2047/
%P 291-297
Markdown (Informal)
[Cutting-off Redundant Repeating Generations for Neural Abstractive Summarization](https://aclanthology.org/E17-2047/) (Suzuki & Nagata, EACL 2017)
ACL