{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T23:39:09Z","timestamp":1767137949206,"version":"build-2238731810"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031446986","type":"print"},{"value":"9783031446993","type":"electronic"}],"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\/978-3-031-44699-3_11","type":"book-chapter","created":{"date-parts":[[2023,10,7]],"date-time":"2023-10-07T04:02:39Z","timestamp":1696651359000},"page":"111-122","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Numeracy-Enhanced Decoding for\u00a0Solving Math Word Problem"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1208-3950","authenticated-orcid":false,"given":"Rao","family":"Peng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5752-7647","authenticated-orcid":false,"given":"Chuanzhi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4850-2635","authenticated-orcid":false,"given":"Litian","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8299-1896","authenticated-orcid":false,"given":"Xiaopan","family":"Lyu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3380-3179","authenticated-orcid":false,"given":"Hao","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8379-6742","authenticated-orcid":false,"given":"Xinguo","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,8]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Amini, A., Gabriel, S., Lin, S., Koncel-Kedziorski, R., Choi, Y., Hajishirzi, H.: MathQA: towards interpretable math word problem solving with operation-based formalisms. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 2357\u20132367 (2019)","DOI":"10.18653\/v1\/N19-1245"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Bobrow, D.G.: A question-answering system for high school algebra word problems. In: Proceedings of the 1964 Fall Joint Computer Conference, pp. 591\u2013614 (1964)","DOI":"10.1145\/1464052.1464108"},{"key":"11_CR3","doi-asserted-by":"publisher","first-page":"3504","DOI":"10.1109\/TASLP.2021.3124365","volume":"29","author":"Y Cui","year":"2021","unstructured":"Cui, Y., Che, W., Liu, T., Qin, B., Yang, Z.: Pre-training with whole word masking for Chinese BERT. IEEE\/ACM Trans. Audio Speech Lang. Process. 29, 3504\u20133514 (2021)","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"key":"11_CR4","unstructured":"Hu, E.J., et al.: LoRA: low-rank adaptation of large language models. arXiv:2106.09685 (2021)"},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Jie, Z., Li, J., Lu, W.: Learning to reason deductively: math word problem solving as complex relation extraction. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, pp. 5944\u20135955 (2022)","DOI":"10.18653\/v1\/2022.acl-long.410"},{"key":"11_CR6","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1037\/0033-295X.92.1.109","volume":"92","author":"W Kintsch","year":"1985","unstructured":"Kintsch, W., Greeno, J.G.: Understanding and solving word arithmetic problems. Psychol. Rev. 92, 109 (1985)","journal-title":"Psychol. Rev."},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Kushman, N., Artzi, Y., Zettlemoyer, L., Barzilay, R.: Learning to automatically solve algebra word problems. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, pp. 271\u2013281 (2014)","DOI":"10.3115\/v1\/P14-1026"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Li, Z., et al.: Seeking patterns, not just memorizing procedures: contrastive learning for solving math word problems. In: Findings of the Association for Computational Linguistics, NAACL 2022, pp. 2486\u20132496 (2022)","DOI":"10.18653\/v1\/2022.findings-acl.195"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Liang, Z., et al.: MWP-BERT: numeracy-augmented pre-training for math word problem solving. In: Findings of the Association for Computational Linguistics, NAACL 2022, pp. 997\u20131009 (2022)","DOI":"10.18653\/v1\/2022.findings-naacl.74"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Liang, Z., Zhang, J., Zhang, X.: Analogical math word problems solving with enhanced problem-solution association. arXiv:2212.00837 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.643"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Lin, X., et al.: Learning relation-enhanced hierarchical solver for math word problems. IEEE Trans. Neural Netw. Learn. Syst. (2023, early access)","DOI":"10.1109\/TNNLS.2023.3272114"},{"key":"11_CR12","doi-asserted-by":"crossref","unstructured":"Lin, X., et al.: HMS: a hierarchical solver with dependency-enhanced understanding for math word problem. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence, pp. 4232\u20134240 (2021)","DOI":"10.1609\/aaai.v35i5.16547"},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Liu, Q., Guan, W., Li, S., Kawahara, D.: Tree-structured decoding for solving math word problems. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing, pp. 2370\u20132379 (2019)","DOI":"10.18653\/v1\/D19-1241"},{"key":"11_CR14","unstructured":"Mor, G., Ankit, G., Jonathan, B.: Injecting numerical reasoning skills into language models. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 946\u2013958 (2020)"},{"key":"11_CR15","first-page":"5485","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21, 5485\u20135551 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Roy, S., Roth, D.: Unit dependency graph and its application to arithmetic word problem solving. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence, pp. 3082\u20133088 (2017)","DOI":"10.1609\/aaai.v31i1.10959"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Shen, J., et al.: Generate & rank: a multi-task framework for math word problems. In: Findings of the Association for Computational Linguistics, EMNLP 2021, pp. 2269\u20132279 (2021)","DOI":"10.18653\/v1\/2021.findings-emnlp.195"},{"key":"11_CR18","doi-asserted-by":"crossref","unstructured":"Shi, S., Wang, Y., Lin, C.Y., Liu, X., Rui, Y.: Automatically solving number word problems by semantic parsing and reasoning. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1132\u20131142 (2015)","DOI":"10.18653\/v1\/D15-1135"},{"key":"11_CR19","unstructured":"Touvron, H., et al.: LLaMA: open and efficient foundation language models. arXiv arXiv:2302.13971 (2023)"},{"key":"11_CR20","doi-asserted-by":"crossref","unstructured":"Wang, L., Wang, Y., Cai, D., Zhang, D., Liu, X.: Translating a math word problem to an expression tree. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 1064\u20131069 (2018)","DOI":"10.18653\/v1\/D18-1132"},{"key":"11_CR21","doi-asserted-by":"crossref","unstructured":"Wang, Y., Liu, X., Shi, S.: Deep neural solver for math word problems. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 845\u2013854 (2017)","DOI":"10.18653\/v1\/D17-1088"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Wu, Q., Zhang, Q., Wei, Z.: An edge-enhanced hierarchical graph-to-tree network for math word problem solving. In: Findings of the Association for Computational Linguistics, EMNLP 2021, pp. 1473\u20131482 (2021)","DOI":"10.18653\/v1\/2021.findings-emnlp.127"},{"key":"11_CR23","doi-asserted-by":"crossref","unstructured":"Xie, Z., Sun, S.: A goal-driven tree-structured neural model for math word problems. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence, pp. 5299\u20135305 (2019)","DOI":"10.24963\/ijcai.2019\/736"},{"key":"11_CR24","doi-asserted-by":"crossref","unstructured":"Yu, X., Wang, M., Gan, W., He, B., Ye, N.: A framework for solving explicit arithmetic word problems and proving plane geometry theorems. Int. J. Pattern Recognit. Artif. Intell. 33, 1940005:1\u20131940005:21 (2019)","DOI":"10.1142\/S0218001419400056"},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, J., et al.: Teacher-student networks with multiple decoders for solving math word problem. In: Proceedings of the 29th International Joint Conference on Artificial Intelligence, pp. 4011\u20134017 (2020)","DOI":"10.24963\/ijcai.2020\/555"},{"key":"11_CR26","doi-asserted-by":"crossref","unstructured":"Zhang, J., et al.: Graph-to-tree learning for solving math word problems. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 3928\u20133937 (2020)","DOI":"10.18653\/v1\/2020.acl-main.362"}],"updated-by":[{"DOI":"10.1007\/978-3-031-44699-3_38","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2023,10,29]],"date-time":"2023-10-29T00:00:00Z","timestamp":1698537600000}}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-44699-3_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T04:48:52Z","timestamp":1730263732000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-44699-3_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031446986","9783031446993"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-44699-3_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"8 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"29 October 2023","order":2,"name":"change_date","label":"Change Date","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Correction","order":3,"name":"change_type","label":"Change Type","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"A correction has been published.","order":4,"name":"change_details","label":"Change Details","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Foshan","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":"12 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2023\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Softconf","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"478","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":"143","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":"0","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":"30% - 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":"4","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)"}}]}}