{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:40:40Z","timestamp":1742935240727,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819757787"},{"type":"electronic","value":"9789819757794"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-97-5779-4_35","type":"book-chapter","created":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T07:16:44Z","timestamp":1736493404000},"page":"486-495","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SGDG: Improving Transformer Seq2Seq Models through Span Generation and Denoise Generation"],"prefix":"10.1007","author":[{"given":"Zhenfei","family":"Yang","sequence":"first","affiliation":[]},{"given":"Beiming","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Chenxiao","family":"Dou","sequence":"additional","affiliation":[]},{"given":"Qian","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yansong","family":"Chua","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,11]]},"reference":[{"key":"35_CR1","doi-asserted-by":"crossref","unstructured":"Cui, Y., Liu, T., Che, W., Xiao, L., Chen, Z., Ma, W., Wang, S., Hu, G.: A span-extraction dataset for Chinese machine reading comprehension. In: Proceedings of the EMNLP-IJCNLP. pp. 5886\u20135891 (2019)","DOI":"10.18653\/v1\/D19-1600"},{"key":"35_CR2","unstructured":"Driess, D., Xia, F., Sajjadi, M.S., Lynch, C., Chowdhery, A., Ichter, B., Wahid, A., Tompson, J., Vuong, Q., Yu, T., et\u00a0al.: Palm-e: An embodied multimodal language model. arXiv preprint arXiv:2303.03378 (2023)"},{"key":"35_CR3","doi-asserted-by":"crossref","unstructured":"Freitag, M., Al-Onaizan, Y.: Beam search strategies for neural machine translation. In: Workshop on Neural Machine Translation. pp. 56\u201360 (2017)","DOI":"10.18653\/v1\/W17-3207"},{"key":"35_CR4","doi-asserted-by":"crossref","unstructured":"Goodman, S., Ding, N., Soricut, R.: Teaforn: Teacher-forcing with n-grams. In: Proceedings of the EMNLP. pp. 8704\u20138717 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.702"},{"key":"35_CR5","unstructured":"Kenton, J.D.M.W.C., Toutanova, L.K.: BERT: Pre-training of deep bidirectional transformers for language understanding. In: NAACL-HLT. p.\u00a02 (2019)"},{"key":"35_CR6","doi-asserted-by":"crossref","unstructured":"Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., Zettlemoyer, L.: BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In: Proceedings of the ACL. pp. 7871\u20137880 (2020)","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"35_CR7","unstructured":"Li, Y., Zhang, Y., Zhao, Z., Shen, L., Liu, W., Mao, W., Zhang, H.: CSL: A large-scale Chinese scientific literature dataset. In: Proceedings of the International Conference on Computational Linguistics. pp. 3917\u20133923 (2022)"},{"key":"35_CR8","unstructured":"Liu, H., Geng, X., Lee, L., Mordatch, I., Levine, S., Narang, S., Abbeel, P.: Fcm: Forgetful causal masking makes causal language models better zero-shot learners. arXiv preprint arXiv:2210.13432 (2022)"},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Liu, Y., Feng, S., Wang, D., Zhang, Y., Sch\u00fctze, H.: PVGRU: Generating diverse and relevant dialogue responses via pseudo-variational mechanism. In: Proceedings of the ACL. pp. 3295\u20133310 (2023)","DOI":"10.18653\/v1\/2023.acl-long.185"},{"key":"35_CR10","doi-asserted-by":"crossref","unstructured":"Qi, W., Yan, Y., Gong, Y., Liu, D., Duan, N., Chen, J., Zhang, R., Zhou, M.: Prophetnet: Predicting future n-gram for sequence-to-sequencepre-training. In: Findings of the EMNLP. pp. 2401\u20132410 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.217"},{"key":"35_CR11","doi-asserted-by":"crossref","unstructured":"Rajpurkar, P., Zhang, J., Lopyrev, K., Liang, P.: Squad: 100,000+ questions for machine comprehension of text. In: EMNLP. pp. 2383\u20132392 (2016)","DOI":"10.18653\/v1\/D16-1264"},{"key":"35_CR12","doi-asserted-by":"crossref","unstructured":"Song, Y., Tian, Y., Wang, N., Xia, F.: Summarizing medical conversations via identifying important utterances. In: Proceedings of the International Conference on Computational Linguistics. pp. 717\u2013729 (2020)","DOI":"10.18653\/v1\/2020.coling-main.63"},{"key":"35_CR13","unstructured":"Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.A., Lacroix, T., Rozi\u00e8re, B., Goyal, N., Hambro, E., Azhar, F., et\u00a0al.: Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023)"},{"key":"35_CR14","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. In: Advances in NeurIPS. vol.\u00a030 (2017)"},{"key":"35_CR15","doi-asserted-by":"crossref","unstructured":"Wang, Z., Wang, J., Jiang, C.: Unified multimodal model with unlikelihood training for visual dialog. In: Proceedings of the ACM International Conference on Multimedia. pp. 4625\u20134634 (2022)","DOI":"10.1145\/3503161.3547974"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5779-4_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T08:12:19Z","timestamp":1736496739000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5779-4_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819757787","9789819757794"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5779-4_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"11 January 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gifu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2024a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.dasfaa2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}