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        <title>Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus</title>
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        <namePart type="given">Wei</namePart>
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    <name type="personal">
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        <namePart type="family">Huang</namePart>
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    <name type="personal">
        <namePart type="given">Yinan</namePart>
        <namePart type="family">Liu</namePart>
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            <title>Proceedings of the Workshop MultiLing 2019: Summarization Across Languages, Genres and Sources</title>
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    <abstract>MultiLing 2019 Headline Generation Task on Wikipedia Corpus raised a critical and practical problem: multilingual task on low resource corpus. In this paper we proposed QDAS extractive summarization model enhanced by sentence2vec and try to apply transfer learning based on large multilingual pre-trained language model for Wikipedia Headline Generation task. We treat it as sequence labeling task and develop two schemes to handle with it. Experimental results have shown that large pre-trained model can effectively utilize learned knowledge to extract certain phrase using low resource supervised data.</abstract>
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%0 Conference Proceedings
%T Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus
%A Liu, Wei
%A Li, Lei
%A Huang, Zuying
%A Liu, Yinan
%Y Giannakopoulos, George
%S Proceedings of the Workshop MultiLing 2019: Summarization Across Languages, Genres and Sources
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F liu-etal-2019-multi-lingual
%X MultiLing 2019 Headline Generation Task on Wikipedia Corpus raised a critical and practical problem: multilingual task on low resource corpus. In this paper we proposed QDAS extractive summarization model enhanced by sentence2vec and try to apply transfer learning based on large multilingual pre-trained language model for Wikipedia Headline Generation task. We treat it as sequence labeling task and develop two schemes to handle with it. Experimental results have shown that large pre-trained model can effectively utilize learned knowledge to extract certain phrase using low resource supervised data.
%R 10.26615/978-954-452-058-8_004
%U https://aclanthology.org/W19-8904
%U https://doi.org/10.26615/978-954-452-058-8_004
%P 17-25

Markdown (Informal)

[Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus](https://aclanthology.org/W19-8904) (Liu et al., RANLP 2019)

• Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus (Liu et al., RANLP 2019)

ACL

• Wei Liu, Lei Li, Zuying Huang, and Yinan Liu. 2019. Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus. In Proceedings of the Workshop MultiLing 2019: Summarization Across Languages, Genres and Sources, pages 17–25, Varna, Bulgaria. INCOMA Ltd..