{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T02:59:50Z","timestamp":1742957990507,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":28,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819947515"},{"type":"electronic","value":"9789819947522"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-981-99-4752-2_49","type":"book-chapter","created":{"date-parts":[[2023,7,30]],"date-time":"2023-07-30T16:02:10Z","timestamp":1690732930000},"page":"597-608","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Nucleus Beam Search for Machine Translation Decoding"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4013-3492","authenticated-orcid":false,"given":"Zheng","family":"Chen","sequence":"first","affiliation":[]},{"given":"Ruiwen","family":"Tao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7425-1182","authenticated-orcid":false,"given":"Yifan","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,31]]},"reference":[{"key":"49_CR1","unstructured":"Boulanger-Lewandowski, N., Bengio, Y., Vincent, P.: Audio chord recognition with recurrent neural networks. In: Proceedings of the 14th International Society for Music Information Retrieval Conference, ISMIR 2013 pp. 335\u2013340 (2013)"},{"key":"49_CR2","unstructured":"Caccia, M., Caccia, L., Fedus, W., Larochelle, H., Pineau, J., Charlin, L.: Language GANs falling short. In: Proceedings of the 8th International Conference on Learning Representations (2020). http:\/\/arxiv.org\/abs\/1811.02549"},{"key":"49_CR3","unstructured":"Cohen, E., Beck, J.C.: Empirical analysis of beam search performance degradation in neural sequence models. In: 36th International Conference on Machine Learning, ICML 2019 2019-June, pp. 2294\u20132312 (2019)"},{"key":"49_CR4","doi-asserted-by":"crossref","unstructured":"Fan, A., Lewis, M., Dauphin, Y.: Hierarchical neural story generation. ACL 2018- 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) 1, 889\u2013898 (2018)","DOI":"10.18653\/v1\/P18-1082"},{"key":"49_CR5","unstructured":"Feng, V.W., Hirst, G.: Text-level discourse parsing with rich linguistic features. In: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 60\u201368 (2012)"},{"key":"49_CR6","doi-asserted-by":"crossref","unstructured":"Ficler, J., Goldberg, Y.: Controlling linguistic style aspects in neural language generation. In: Proceedings of the Workshop on Stylistic Variation, pp. 94\u2013104 (2017)","DOI":"10.18653\/v1\/W17-4912"},{"key":"49_CR7","unstructured":"Graves, A.: Sequence Transduction with Recurrent Neural Networks. arXiv preprint arXiv:1211.3711 (2012). http:\/\/arxiv.org\/abs\/1211.3711"},{"key":"49_CR8","doi-asserted-by":"crossref","unstructured":"He, W., He, Z., Wu, H., Wang, H.: Improved neural machine translation with SMT features. In: 30th AAAI Conference on Artificial Intelligence, AAAI 2016, no. 10, pp.151\u2013157 (2016)","DOI":"10.1609\/aaai.v30i1.9983"},{"key":"49_CR9","unstructured":"Holtzman, A., Buys, J., Du, L., Forbes, M., Choi, Y.: The curious case of neural text degeneration. In: The International Conference on Learning Representations (ICLR) (2020)"},{"key":"49_CR10","first-page":"849","volume":"19","author":"T Jaeger","year":"2007","unstructured":"Jaeger, T., Levy, R.: Speakers optimize information density through syntactic reduction. Adv. Neural. Inf. Process. Syst. 19, 849\u2013856 (2007)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"49_CR11","doi-asserted-by":"crossref","unstructured":"Jean, S., Firat, O., Cho, K., Memisevic, R., Bengio, Y.: Montreal neural machine translation systems for wmt\u201915. In: 10th Workshop on Statistical Machine Translation, WMT 2015 at the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 \u2013 Proceedings, pp. 134\u2013140 (2015)","DOI":"10.18653\/v1\/W15-3014"},{"key":"49_CR12","doi-asserted-by":"crossref","unstructured":"Koehn, P., Knowles, R.: Six Challenges for Neural Machine Translation. First Workshop on Neural Machine Translation pp. 28\u201339 (2017)","DOI":"10.18653\/v1\/W17-3204"},{"key":"49_CR13","doi-asserted-by":"crossref","unstructured":"Lukasik, M., et al.: Semantic label smoothing for sequence to sequence problems. In: EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (2016), pp. 4992\u20134998 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.405"},{"key":"49_CR14","doi-asserted-by":"crossref","unstructured":"Luong, M.T., Sutskever, I., Le, Q.V., Vinyals, O., Zaremba, W.: Addressing the rare word problem in neural machine translation. In: ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th Inter- national Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference, vol. 1, pp. 11\u201319 (2015)","DOI":"10.3115\/v1\/P15-1002"},{"key":"49_CR15","doi-asserted-by":"crossref","unstructured":"Meister, C., Cotterell, R., Vieira, T.: If beam search is the answer, what was the question? In: EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, pp. 2173\u20132185 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.170"},{"key":"49_CR16","doi-asserted-by":"crossref","unstructured":"Meister, C., Pimentel, T., Haller, P., J\u00e4ger, L., Cotterell, R., Levy, R.: Revisiting the uniform information density hypothesis. In: EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (i), pp. 963\u2013980 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.74"},{"issue":"23","key":"49_CR17","doi-asserted-by":"publisher","first-page":"15919","DOI":"10.1007\/s00521-021-06268-0","volume":"33","author":"SA Mohamed","year":"2021","unstructured":"Mohamed, S.A., Elsayed, A.A., Hassan, Y.F., Abdou, M.A.: Neural machine translation: past, present, and future. Neural Comput. Appl. 33(23), 15919\u201315931 (2021). https:\/\/doi.org\/10.1007\/s00521-021-06268-0","journal-title":"Neural Comput. Appl."},{"key":"49_CR18","doi-asserted-by":"crossref","unstructured":"Murray, K., Chiang, D.: Correcting length bias in neural machine translation. In: WMT 2018 - 3rd Conference on Machine Translation, Proceedings of the Conference, vol. 1, pp. 212\u2013223 (2018)","DOI":"10.18653\/v1\/W18-6322"},{"key":"49_CR19","doi-asserted-by":"crossref","unstructured":"Peters, B., Martins, A.F.T.: Smoothing and shrinking the Sparse Seq2Seq search space. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 2642\u20132654 (2021)","DOI":"10.18653\/v1\/2021.naacl-main.210"},{"key":"49_CR20","doi-asserted-by":"publisher","unstructured":"Shaham, U., Levy, O.: What do you get when you cross beam search with nucleus sampling? In: Proceedings of the Third Workshop on Insights from Negative Results in NLP, Dublin, Ireland, pp. 38\u201345. Association for Computational Linguistics, May 2022. https:\/\/doi.org\/10.18653\/v1\/2022.insights-1.5, https:\/\/aclanthology.org\/2022.insights-1.5","DOI":"10.18653\/v1\/2022.insights-1.5"},{"issue":"3","key":"49_CR21","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1016\/j.cognition.2013.02.013","volume":"128","author":"NJ Smith","year":"2013","unstructured":"Smith, N.J., Levy, R.: The effect of word predictability on reading time is logarithmic. Cognition 128(3), 302\u2013319 (2013)","journal-title":"Cognition"},{"key":"49_CR22","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1613\/jair.1.12007","volume":"69","author":"F Stahlberg","year":"2020","unstructured":"Stahlberg, F.: Neural machine translation: a review. J. Artif. Intell. Res. 69, 343\u2013418 (2020)","journal-title":"J. Artif. Intell. Res."},{"key":"49_CR23","doi-asserted-by":"crossref","unstructured":"Stahlberg, F., Byrne, B.: On NMT search errors and model errors: cat got your tongue? In: EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference, pp. 3356\u20133362 (2019)","DOI":"10.18653\/v1\/D19-1331"},{"key":"49_CR24","unstructured":"Tiedemann, J., Thottingal, S.: OPUS-MT \u2014 building open translation services for the world. In: Proceedings of the 22nd Annual Conference of the European Association for Machine Translation (EAMT). Lisbon, Portugal (2020)"},{"key":"49_CR25","unstructured":"Tily, H., Piantadosi, S.: Refer efficiently: Use less informative expressions for more predictable meanings. In: Proceedings of the Workshop on the Production of Referring Expressions: Bridging the Gap Between Computational and Empirical Approaches to Reference (2009)"},{"key":"49_CR26","unstructured":"Wu, Y., et al.: Google\u2019s neural machine translation system: bridging the gap between human and machine translation. arXiv preprint arXiv:1609.08144 pp. 1\u201323 (2016). http:\/\/arxiv.org\/abs\/1609.08144"},{"key":"49_CR27","unstructured":"Yang, S., Wang, Y., Chu, X.: A survey of deep learning techniques for neural machine translation. arXiv preprint arXiv:2002.07526 (2020). http:\/\/arxiv.org\/abs\/2002.07526"},{"key":"49_CR28","doi-asserted-by":"crossref","unstructured":"Yang, Y., Huang, L., Ma, M.: Breaking the beam search curse: a study of (re)scoring methods and stopping criteria for neural machine translation. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, pp. 3054\u20133059 (2018)","DOI":"10.18653\/v1\/D18-1342"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-4752-2_49","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T23:14:43Z","timestamp":1690931683000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-4752-2_49"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819947515","9789819947522"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-4752-2_49","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"31 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhengzhou","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2023\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}