{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:25:17Z","timestamp":1783103117339,"version":"3.54.6"},"publisher-location":"Singapore","reference-count":36,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819533459","type":"print"},{"value":"9789819533466","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T00:00:00Z","timestamp":1763856000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T00:00:00Z","timestamp":1763856000000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-3346-6_22","type":"book-chapter","created":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T05:49:47Z","timestamp":1763790587000},"page":"289-300","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MQA-SQL: Mitigating Question Ambiguity in Text-to-SQL with Multi-model Collaboration and Multi-variant Query Rephrasing"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-5003-2427","authenticated-orcid":false,"given":"Yiming","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7055-0767","authenticated-orcid":false,"given":"Jiyu","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4073-1214","authenticated-orcid":false,"given":"Jichuan","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4774-2434","authenticated-orcid":false,"given":"Cuiyun","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiyi","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuanyi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,23]]},"reference":[{"issue":"1","key":"22_CR1","first-page":"1","volume":"36","author":"W Zhong","year":"2024","unstructured":"Zhong, W., She, Q., Zhou, C.: Intelligent customer service system optimization based on artificial intelligence. J. Organ. End User Comput. (JOEUC) 36(1), 1\u201327 (2024)","journal-title":"J. Organ. End User Comput. (JOEUC)"},{"key":"22_CR2","unstructured":"Liu, X., et al.: A survey of NL2SQL with large language models: where are we, and where are we going? arXiv preprint arXiv:2408.05109 (2024)"},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"SY Kim, S., Liao, Q.V., Vorvoreanu, M., Ballard, S., Vaughan, J.W.: \" I\u2019m not sure, but...\": examining the impact of large language models\u2019 uncertainty expression on user reliance and trust. In: The 2024 ACM Conference on Fairness, Accountability, and Transparency, pp. 822\u2013835 (2024)","DOI":"10.1145\/3630106.3658941"},{"key":"22_CR4","doi-asserted-by":"crossref","unstructured":"Guo, C., et al.: Retrieval-augmented GPT-3.5-based text-to-SQL framework with sample-aware prompting and dynamic revision chain. In: International Conference on Neural Information Processing, pp. 341\u2013356. Springer (2023)","DOI":"10.1007\/978-981-99-8076-5_25"},{"key":"22_CR5","first-page":"2009","volume":"2024","author":"W Mao","year":"2024","unstructured":"Mao, W., et al.: Enhancing text-to-SQL parsing through question rewriting and execution-guided refinement. Find. Assoc. Comput. Ling. ACL 2024, 2009\u20132024 (2024)","journal-title":"Find. Assoc. Comput. Ling. ACL"},{"key":"22_CR6","unstructured":"Cafero\u011flu, H.P., Ulusoy, O.: E-SQL: direct schema linking via question enrichment in text-to-SQL. arXiv preprint arXiv:2409.16751 (2024)"},{"issue":"3","key":"22_CR7","first-page":"1","volume":"2","author":"H Li","year":"2024","unstructured":"Li, H., et al.: Codes: towards building open-source language models for text-to-SQL. Proc. ACM Manag. Data 2(3), 1\u201328 (2024)","journal-title":"Proc. ACM Manag. Data"},{"key":"22_CR8","doi-asserted-by":"crossref","unstructured":"Kukreja, S., Kumar, T., Purohit, A., Dasgupta, A., Guha, D.: A literature survey on open source large language models. In: Proceedings of the 2024 7th International Conference on Computers in Management and Business, pp. 133\u2013143 (2024)","DOI":"10.1145\/3647782.3647803"},{"key":"22_CR9","doi-asserted-by":"crossref","unstructured":"Jiang, W., Han, J., Liu, H., Tao, T., Tan, N., Xiong, H.: Interpretable cascading mixture-of-experts for urban traffic congestion prediction. In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 5206\u20135217 (2024)","DOI":"10.1145\/3637528.3671507"},{"key":"22_CR10","unstructured":"Jiang, J., Wang, F., Shen, J., Kim, S., Kim, S.: A survey on large language models for code generation. arXiv preprint arXiv:2406.00515 (2024)"},{"key":"22_CR11","unstructured":"Wang, J., Wang, J., Athiwaratkun, B., Zhang, C., Zou, J.: Mixture-of-agents enhances large language model capabilities. arXiv preprint arXiv:2406.04692 (2024)"},{"key":"22_CR12","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Zhu, Y., Antognini, D., Kim, Y., Zhang, Y.: Paraphrase and solve: exploring and exploiting the impact of surface form on mathematical reasoning in large language models. In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pp. 2793\u20132804 (2024)","DOI":"10.18653\/v1\/2024.naacl-long.153"},{"key":"22_CR13","unstructured":"Sun, Q., Yin, Z., Li, X., Wu, Z., Qiu, X., Kong, L.: Corex: pushing the boundaries of complex reasoning through multi-model collaboration. In: ICLR 2024 Workshop on Large Language Model (LLM) Agents (2024)"},{"key":"22_CR14","unstructured":"Touvron, H., et\u00a0al.: Llama 2: open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288 (2023)"},{"key":"22_CR15","unstructured":"Guo, D., et al.: DeepSeek-coder: when the large language model meets programming \u2013 the rise of code intelligence. arXiv preprint arXiv:2401.14196 (2024)"},{"key":"22_CR16","unstructured":"Liu, A., Hu, X., Wen, L., Yu, P.S.: A comprehensive evaluation of ChatGPT\u2019s zero-shot text-to-SQL capability. arXiv preprint arXiv:2303.13547 (2023)"},{"key":"22_CR17","doi-asserted-by":"crossref","unstructured":"Yu, T., et\u00a0al.: Spider: a large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3911\u20133921 (2018)","DOI":"10.18653\/v1\/D18-1425"},{"key":"22_CR18","doi-asserted-by":"crossref","unstructured":"Li, J., et\u00a0al.: Can LLM already serve as a database interface? A big bench for large-scale database grounded text-to-SQLs. Adv. Neural Info. Process. Syst. 36 (2024)","DOI":"10.52202\/075280-1835"},{"key":"22_CR19","doi-asserted-by":"crossref","unstructured":"Gan, Y., Chen, X., Purver, M.: Exploring underexplored limitations of cross-domain text-to-SQL generalization. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 8926\u20138931 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.702"},{"key":"22_CR20","doi-asserted-by":"crossref","unstructured":"Gan, Y., et al.: Towards robustness of text-to-SQL models against synonym substitution. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL\/IJCNLP 2021, pp. 2505\u20132515 (2021)","DOI":"10.18653\/v1\/2021.acl-long.195"},{"key":"22_CR21","doi-asserted-by":"crossref","unstructured":"Deng, X., Awadallah, A.H., Meek, C., Polozov, O., Sun, H., Richardson, M.: Structure-grounded pretraining for text-to-SQL. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021, pp. 1337\u20131350 (2021)","DOI":"10.18653\/v1\/2021.naacl-main.105"},{"key":"22_CR22","unstructured":"Luo, Z., et al.: WizardCoder: empowering code large language models with evol-instruct. In: The Twelfth International Conference on Learning Representations (2023)"},{"key":"22_CR23","unstructured":"Pinnaparaju, N., et\u00a0al.: Stable code technical report. arXiv preprint arXiv:2404.01226 (2024)"},{"key":"22_CR24","doi-asserted-by":"crossref","unstructured":"Zhou, P., Xie, X., Lin, Z., Yan, S.: Towards understanding convergence and generalization of AdamW. IEEE Trans. Pattern Anal. Mach. Intell. (2024)","DOI":"10.1109\/TPAMI.2024.3382294"},{"key":"22_CR25","unstructured":"Hurst, A., et\u00a0al.: GPT-4o system card. arXiv preprint arXiv:2410.21276 (2024)"},{"key":"22_CR26","doi-asserted-by":"crossref","unstructured":"Zhong, R., Yu, T., Klein, D.: Semantic evaluation for text-to-SQL with distilled test suites. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, pp. 396\u2013411 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.29"},{"key":"22_CR27","doi-asserted-by":"crossref","unstructured":"Pourreza, M., Rafiei, D.: DIN-SQL: decomposed in-context learning of text-to-SQL with self-correction. Adv. Neural Info. Process. Syst. 36 (2024)","DOI":"10.52202\/075280-1577"},{"key":"22_CR28","doi-asserted-by":"crossref","unstructured":"Gao, D., et al.: Text-to-SQL empowered by large language models: a benchmark evaluation. In: International Conference on Very Large Data Bases (VLDB) (2024)","DOI":"10.14778\/3641204.3641221"},{"key":"22_CR29","first-page":"10796","volume":"2024","author":"Y Xie","year":"2024","unstructured":"Xie, Y., et al.: Decomposition for enhancing attention: improving LLM-based text-to-SQL through workflow paradigm. Find. Assoc. Comput. Ling. ACL 2024, 10796\u201310816 (2024)","journal-title":"Find. Assoc. Comput. Ling. ACL"},{"key":"22_CR30","unstructured":"Wang, B., et\u00a0al.: MAC-SQL: a multi-agent collaborative framework for text-to-SQL. arXiv preprint arXiv:2312.11242 (2024)"},{"key":"22_CR31","doi-asserted-by":"crossref","unstructured":"Tonghui R., et al.: Purple: making a large language model a better SQL writer. In: 2024 IEEE 40th International Conference on Data Engineering (ICDE), pp. 15\u201328 (2024)","DOI":"10.1109\/ICDE60146.2024.00009"},{"key":"22_CR32","doi-asserted-by":"crossref","unstructured":"Pourreza, M., Rafiei, D.: DTS-SQL: decomposed text-to-SQL with small large language models. arXiv preprint arXiv:2402.01117 (2024)","DOI":"10.18653\/v1\/2024.findings-emnlp.481"},{"key":"22_CR33","doi-asserted-by":"crossref","unstructured":"Yang, J., Hui, B., Yang, M., Yang, J., Lin, J., Zhou, C.: Synthesizing text-to-SQL data from weak and strong LLMs. In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, (vol. 1: Long Papers), pp. 7864\u20137875 (2024)","DOI":"10.18653\/v1\/2024.acl-long.425"},{"key":"22_CR34","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: Self-instruct: aligning language models with self-generated instructions. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, (vol. 1: Long Papers), pp. 13484\u201313508 (2023)","DOI":"10.18653\/v1\/2023.acl-long.754"},{"key":"22_CR35","doi-asserted-by":"crossref","unstructured":"Renze, M., Guven, E.: The effect of sampling temperature on problem solving in large language models. arXiv preprint arXiv:2402.05201 (2024)","DOI":"10.18653\/v1\/2024.findings-emnlp.432"},{"key":"22_CR36","unstructured":"Lee, D., Park, C., Kim, J., Park, H.: MCS-SQL: leveraging multiple prompts and multiple-choice selection for text-to-SQL generation. arXiv preprint arXiv:2405.07467 (2024)"}],"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\/978-981-95-3346-6_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:12:07Z","timestamp":1783102327000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3346-6_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,23]]},"ISBN":["9789819533459","9789819533466"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3346-6_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,23]]},"assertion":[{"value":"23 November 2025","order":1,"name":"first_online","label":"First Online","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":"Urumqi","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2025\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}