{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T02:58:33Z","timestamp":1742957913803,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031149023"},{"type":"electronic","value":"9783031149030"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-14903-0_18","type":"book-chapter","created":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T23:03:00Z","timestamp":1666134180000},"page":"166-173","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Improved Transformer-Based Implicit Latent GAN with Multi-headed Self-attention for Unconditional Text Generation"],"prefix":"10.1007","author":[{"given":"Fuji","family":"Ren","sequence":"first","affiliation":[]},{"given":"Ziyun","family":"Jiao","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Kang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,19]]},"reference":[{"key":"18_CR1","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow, I., et al.: Generative adversarial networks. Commun. ACM 63, 139\u2013144 (2020)","journal-title":"Commun. ACM"},{"key":"18_CR2","unstructured":"Kusner, M.J., Hern\u00e1ndez-Lobato, J.M.: GANs for sequences of discrete elements with the gumbel-softmax distribution. arXiv arXiv:1611.04051 (2016)"},{"key":"18_CR3","unstructured":"Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein GAN. arXiv arXiv:1701.07875 (2017)"},{"key":"18_CR4","doi-asserted-by":"crossref","unstructured":"Diao, S., Shen, X., Shum, K., et al.: TILGAN: transformer-based implicit latent GAN for diverse and coherent text generation. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pp. 4844\u20134858 (2021)","DOI":"10.18653\/v1\/2021.findings-acl.428"},{"key":"18_CR5","unstructured":"Nie, W., Narodytska, N., Patel, A.: RelGAN: relational generative adversarial networks for text generation. In: Proceedings of the International Conference on Learning Representations, Vancouver, BC, Canada, 30 April\u20133 May 2018"},{"key":"18_CR6","doi-asserted-by":"crossref","unstructured":"Yu, L., Zhang, W., Wang, J., Yu, Y.: SeqGAN: sequence generative adversarial nets with policy gradient. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, CA, USA, 4\u20139 February 2017","DOI":"10.1609\/aaai.v31i1.10804"},{"key":"18_CR7","doi-asserted-by":"crossref","unstructured":"Guo, J., Lu, S., Cai, H., Zhang, W., Yu, Y., Wang, J.: Long text generation via adversarial training with leaked information. arXiv arXiv:1709.08624 (2017)","DOI":"10.1609\/aaai.v32i1.11957"},{"key":"18_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-20893-6_1","volume-title":"Computer Vision \u2013 ACCV 2018","author":"F Juefei-Xu","year":"2019","unstructured":"Juefei-Xu, F., Dey, R., Boddeti, V.N., Savvides, M.: RankGAN: a maximum margin ranking GAN for generating faces. In: Jawahar, C.V., Li, H., Mori, G., Schindler, K. (eds.) ACCV 2018. LNCS, vol. 11363, pp. 3\u201318. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-20893-6_1"},{"key":"18_CR9","unstructured":"Fedus, W., Goodfellow, I., Dai, A.M.: MaskGAN: better text generation via filling in the ____. arXiv arXiv:1801.07736 (2018)"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Liu, Z., Wang, J., Liang, Z.: CatGAN: category-aware generative adversarial networks with hierarchical evolutionary learning for category text generation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 05, pp. 8425\u20138432 (2020)","DOI":"10.1609\/aaai.v34i05.6361"},{"key":"18_CR11","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv arXiv:1412.6980 (2014)"},{"key":"18_CR12","doi-asserted-by":"crossref","unstructured":"Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, Philadelphia, PA, USA, 7\u201312 July 2002","DOI":"10.3115\/1073083.1073135"},{"key":"18_CR13","doi-asserted-by":"crossref","unstructured":"Zhu, Y., et al.: Texygen: a benchmarking platform for text generation models. In: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 1097\u20131100 (2018)","DOI":"10.1145\/3209978.3210080"},{"key":"18_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"18_CR15","unstructured":"Chen, L., et al.: Adversarial text generation via feature mover\u2019s distance. In: Advances in Neural Information Processing Systems, pp. 4666\u20134677 (2018)"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"Wu, H.Y., Chen, Y.L.: Graph sparsification with generative adversarial network. In: 2020 IEEE International Conference on Data Mining (ICDM), pp. 1328\u20131333. IEEE (2020)","DOI":"10.1109\/ICDM50108.2020.00172"}],"container-title":["IFIP Advances in Information and Communication Technology","Intelligence Science IV"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-14903-0_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T07:05:35Z","timestamp":1672383935000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-14903-0_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031149023","9783031149030"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-14903-0_18","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"19 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligence Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xi'an","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icis2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.intsci.ac.cn\/icis2022\/home\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","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":"85","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":"44","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":"5","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":"52% - 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":"3","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":"5","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}