https://scholars.lib.ntu.edu.tw/handle/123456789/558975
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, Y.-S. | en_US |
dc.contributor.author | HUNG-YI LEE | en_US |
dc.date.accessioned | 2021-05-05T02:43:09Z | - |
dc.date.available | 2021-05-05T02:43:09Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.url?eid=2-s2.0-85070676881&partnerID=40&md5=2ff5060522271fe88ed14998f67e440c | - |
dc.identifier.uri | https://scholars.lib.ntu.edu.tw/handle/123456789/558975 | - |
dc.description.abstract | Auto-encoders compress input data into a latent-space representation and reconstruct the original data from the representation. This latent representation is not easily interpreted by humans. In this paper, we propose training an auto-encoder that encodes input text into human-readable sentences, and unpaired abstractive summarization is thereby achieved. The auto-encoder is composed of a generator and a reconstructor. The generator encodes the input text into a shorter word sequence, and the reconstructor recovers the generator input from the generator output. To make the generator output human-readable, a discriminator restricts the output of the generator to resemble human-written sentences. By taking the generator output as the summary of the input text, abstractive summarization is achieved without document-summary pairs as training data. Promising results are shown on both English and Chinese corpora. © 2018 Association for Computational Linguistics | - |
dc.relation.ispartof | Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 | - |
dc.subject.other | Encoding (symbols); Learning systems; Network coding; Adversarial networks; Auto encoders; Chinese corpus; Human-readable; Input datas; Training data; Natural language processing systems | - |
dc.title | Learning to encode text as human-readable summaries using generative adversarial networks | en_US |
dc.type | conference paper | en |
dc.identifier.scopus | 2-s2.0-85070676881 | - |
dc.relation.pages | 4187-4195 | - |
item.cerifentitytype | Publications | - |
item.fulltext | no fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_5794 | - |
item.openairetype | conference paper | - |
item.grantfulltext | none | - |
crisitem.author.dept | Electrical Engineering | - |
crisitem.author.dept | Intel-NTU Connected Context Computing Center | - |
crisitem.author.dept | Communication Engineering | - |
crisitem.author.dept | Computer Science and Information Engineering | - |
crisitem.author.dept | Networking and Multimedia | - |
crisitem.author.dept | Center for Artificial Intelligence and Advanced Robotics | - |
crisitem.author.dept | Master's Program in Smart Medicine and Health Informatics (SMARTMHI) | - |
crisitem.author.orcid | 0000-0002-9654-5747 | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
crisitem.author.parentorg | Others: International Research Centers | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
crisitem.author.parentorg | International College | - |
Appears in Collections: | 電機工程學系 |
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