{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T04:13:55Z","timestamp":1749615235873,"version":"3.41.0"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030779634"},{"type":"electronic","value":"9783030779641"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-77964-1_5","type":"book-chapter","created":{"date-parts":[[2021,6,11]],"date-time":"2021-06-11T08:03:43Z","timestamp":1623398623000},"page":"58-71","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Gist Information Guided Neural Network for Abstractive Summarization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8823-866X","authenticated-orcid":false,"given":"Yawei","family":"Kong","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9693-1122","authenticated-orcid":false,"given":"Lu","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Can","family":"Ma","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,9]]},"reference":[{"key":"5_CR1","doi-asserted-by":"publisher","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993\u20131022 (2003). https:\/\/doi.org\/10.1162\/jmlr.2003.3.4-5.993, http:\/\/portal.acm.org\/citation.cfm?id=944937","DOI":"10.1162\/jmlr.2003.3.4-5.993"},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Cao, Z., Li, W., Li, S., Wei, F.: 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), pp. 152\u2013161 (2018)","DOI":"10.18653\/v1\/P18-1015"},{"key":"5_CR3","doi-asserted-by":"publisher","unstructured":"Celikyilmaz, A., Bosselut, A., He, X., Choi, Y.: Deep communicating agents for abstractive summarization. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 1662\u20131675. Association for Computational Linguistics, New Orleans, Louisiana, June 2018. https:\/\/doi.org\/10.18653\/v1\/N18-1150, https:\/\/www.aclweb.org\/anthology\/N18-1150","DOI":"10.18653\/v1\/N18-1150"},{"key":"5_CR4","doi-asserted-by":"publisher","unstructured":"Chen, Y.C., Bansal, M.: Fast abstractive summarization with reinforce-selected sentence rewriting. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 675\u2013686. Association for Computational Linguistics, Melbourne, Australia, July 2018. https:\/\/doi.org\/10.18653\/v1\/P18-1063, https:\/\/www.aclweb.org\/anthology\/P18-1063","DOI":"10.18653\/v1\/P18-1063"},{"key":"5_CR5","doi-asserted-by":"publisher","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186. Association for Computational Linguistics, Minneapolis, Minnesota, June 2019. https:\/\/doi.org\/10.18653\/v1\/N19-1423, https:\/\/www.aclweb.org\/anthology\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"5_CR6","doi-asserted-by":"publisher","unstructured":"Fan, A., Grangier, D., Auli, M.: Controllable abstractive summarization. In: Proceedings of the 2nd Workshop on Neural Machine Translation and Generation. pp. 45\u201354. Association for Computational Linguistics, Melbourne, Australia, July 2018. https:\/\/doi.org\/10.18653\/v1\/W18-2706, https:\/\/www.aclweb.org\/anthology\/W18-2706","DOI":"10.18653\/v1\/W18-2706"},{"key":"5_CR7","doi-asserted-by":"publisher","unstructured":"Gehrmann, S., Deng, Y., Rush, A.: Bottom-up abstractive summarization. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 4098\u20134109. Association for Computational Linguistics, Brussels, Belgium, October\u2013November 2018. https:\/\/doi.org\/10.18653\/v1\/D18-1443, https:\/\/www.aclweb.org\/anthology\/D18-1443","DOI":"10.18653\/v1\/D18-1443"},{"key":"5_CR8","doi-asserted-by":"publisher","unstructured":"Gui, M., Tian, J., Wang, R., Yang, Z.: Attention optimization for abstractive document summarization. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, 3\u20137 November 2019, pp. 1222\u20131228 (2019). https:\/\/doi.org\/10.18653\/v1\/D19-1117, https:\/\/doi.org\/10.18653\/v1\/D19-1117","DOI":"10.18653\/v1\/D19-1117"},{"key":"5_CR9","unstructured":"Hermann, K.M., Kocisky, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., Blunsom, P.: Teaching machines to read and comprehend. In: Advances in Neural Information Processing Systems, pp. 1693\u20131701 (2015)"},{"key":"5_CR10","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: Bengio, Y., LeCun, Y. (eds.) 3rd International Conference on Learning Representations, ICLR 2015, Conference Track Proceedings , San Diego, CA, USA, 7\u20139 May 2015 (2015)"},{"key":"5_CR11","doi-asserted-by":"publisher","unstructured":"Krishna, K., Srinivasan, B.V.: Generating topic-oriented summaries using neural attention. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 1697\u20131705. Association for Computational Linguistics, New Orleans, Louisiana, June 2018. https:\/\/doi.org\/10.18653\/v1\/N18-1153, https:\/\/www.aclweb.org\/anthology\/N18-1153","DOI":"10.18653\/v1\/N18-1153"},{"key":"5_CR12","doi-asserted-by":"publisher","unstructured":"Li, C., Xu, W., Li, S., Gao, S.: Guiding generation for abstractive text summarization based on key information guide network. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pp. 55\u201360. Association for Computational Linguistics, New Orleans, Louisiana, June 2018. https:\/\/doi.org\/10.18653\/v1\/N18-2009, https:\/\/www.aclweb.org\/anthology\/N18-2009","DOI":"10.18653\/v1\/N18-2009"},{"key":"5_CR13","unstructured":"Lin, C.Y.: Rouge: a package for automatic evaluation of summaries. In: Workshop on Text Summarization Branches Out, Post-Conference Workshop of ACL 2004, Barcelona, Spain, July 2004. https:\/\/www.microsoft.com\/en-us\/research\/publication\/rouge-a-package-for-automatic-evaluation-of-summaries\/"},{"key":"5_CR14","unstructured":"Nallapati, R., Xiang, B., Zhou, B.: Sequence-to-sequence RNNs for text summarization. ArXiv abs\/1602.06023 (2016)"},{"key":"5_CR15","doi-asserted-by":"publisher","unstructured":"Pasunuru, R., Bansal, M.: Multi-reward reinforced summarization with saliency and entailment. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pp. 646\u2013653. Association for Computational Linguistics, New Orleans, Louisiana, June 2018. https:\/\/doi.org\/10.18653\/v1\/N18-2102, https:\/\/www.aclweb.org\/anthology\/N18-2102","DOI":"10.18653\/v1\/N18-2102"},{"key":"5_CR16","unstructured":"Paulus, R., Xiong, C., Socher, R.: A deep reinforced model for abstractive summarization. In: 6th International Conference on Learning Representations, ICLR 2018, Conference Track Proceedings, Vancouver, BC, Canada, 30 April - 3 May 2018, OpenReview.net (2018). https:\/\/openreview.net\/forum?id=HkAClQgA-"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.: Glove: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"5_CR18","doi-asserted-by":"publisher","unstructured":"Perez-Beltrachini, L., Liu, Y., Lapata, M.: Generating summaries with topic templates and structured convolutional decoders. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 5107\u20135116. Association for Computational Linguistics, Florence, Italy, July 2019. https:\/\/doi.org\/10.18653\/v1\/P19-1504, https:\/\/www.aclweb.org\/anthology\/P19-1504","DOI":"10.18653\/v1\/P19-1504"},{"key":"5_CR19","doi-asserted-by":"publisher","unstructured":"Rush, A.M., Chopra, S., Weston, J.: A neural attention model for abstractive sentence summarization. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 379\u2013389. Association for Computational Linguistics, Lisbon, Portugal, September 2015. https:\/\/doi.org\/10.18653\/v1\/D15-1044, https:\/\/www.aclweb.org\/anthology\/D15-1044","DOI":"10.18653\/v1\/D15-1044"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"See, A., Liu, P.J., Manning, C.D.: Get to the point: summarization with pointer-generator networks. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1073\u20131083. Association for Computational Linguistics, Vancouver, Canada, July 2017","DOI":"10.18653\/v1\/P17-1099"},{"key":"5_CR21","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"5_CR22","doi-asserted-by":"crossref","unstructured":"Wang, K., Quan, X., Wang, R.: Biset: bi-directional selective encoding with template for abstractive summarization. arXiv preprint arXiv:1906.05012 (2019)","DOI":"10.18653\/v1\/P19-1207"},{"key":"5_CR23","doi-asserted-by":"publisher","unstructured":"Wang, L., Yao, J., Tao, Y., Zhong, L., Liu, W., Du, Q.: A reinforced topic-aware convolutional sequence-to-sequence model for abstractive text summarization. In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18, pp. 4453\u20134460. International Joint Conferences on Artificial Intelligence Organization, July 2018. https:\/\/doi.org\/10.24963\/ijcai.2018\/619, https:\/\/doi.org\/10.24963\/ijcai.2018\/619","DOI":"10.24963\/ijcai.2018\/619"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"You, Y., Jia, W., Liu, T., Yang, W.: Improving abstractive document summarization with salient information modeling. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 2132\u20132141 (2019)","DOI":"10.18653\/v1\/P19-1205"},{"key":"5_CR25","unstructured":"Zheng, C., Zhang, K., Wang, H.J., Fan, L.: Topic-aware abstractive text summarization (2020)"}],"container-title":["Lecture Notes in Computer Science","Computational Science \u2013 ICCS 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-77964-1_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,10]],"date-time":"2025-06-10T22:02:40Z","timestamp":1749592960000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-77964-1_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030779634","9783030779641"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-77964-1_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"9 June 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Krakow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Poland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 June 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 June 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccs-computsci2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iccs-meeting.org\/iccs2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"156","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"14","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.8","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.9","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"212 full and 43 short papers were selected from 479 submissions to the workshops\/ thematic tracks. The conference was held virtually.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}