{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T09:00:07Z","timestamp":1775638807065,"version":"3.50.1"},"reference-count":51,"publisher":"Association for Computing Machinery (ACM)","issue":"11","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:p>\n            Zero-shot natural language to SQL (NL2SQL) aims to generalize pretrained NL2SQL models to new environments (\n            <jats:italic>e.g.<\/jats:italic>\n            , new databases and new linguistic phenomena) without any annotated NL2SQL samples from these environments. Existing approaches either use small language models (SLMs) like BART and T5, or prompt large language models (LLMs). However, SLMs may struggle with complex natural language reasoning, and LLMs may not precisely align schemas to identify the correct columns or tables. In this paper, we propose a ZeroNL2SQL framework, which divides NL2SQL into smaller sub-tasks and utilizes both SLMs and LLMs. ZeroNL2SQL first fine-tunes SLMs for better generalizability in SQL structure identification and schema alignment, producing an\n            <jats:italic>SQL sketch.<\/jats:italic>\n            It then uses LLMs's language reasoning capability to fill in the missing information in the SQL sketch. To support ZeroNL2SQL, we propose novel database serialization and question-aware alignment methods for effective sketch generation using SLMs. Additionally, we devise a multi-level matching strategy to recommend the most relevant values to LLMs, and select the optimal SQL query via an execution-based strategy. Comprehensive experiments show that ZeroNL2SQL achieves the best zero-shot NL2SQL performance on benchmarks,\n            <jats:italic>i.e.<\/jats:italic>\n            , outperforming the state-of-the-art SLM-based methods by 5.5% to 16.4% and exceeding LLM-based methods by 10% to 20% on execution accuracy.\n          <\/jats:p>","DOI":"10.14778\/3681954.3681960","type":"journal-article","created":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T16:23:36Z","timestamp":1725035016000},"page":"2750-2763","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":26,"title":["Combining Small Language Models and Large Language Models for Zero-Shot NL2SQL"],"prefix":"10.14778","volume":"17","author":[{"given":"Ju","family":"Fan","sequence":"first","affiliation":[{"name":"Renmin University of China"}]},{"given":"Zihui","family":"Gu","sequence":"additional","affiliation":[{"name":"Renmin University of China"}]},{"given":"Songyue","family":"Zhang","sequence":"additional","affiliation":[{"name":"Renmin University of China"}]},{"given":"Yuxin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Renmin University of China"}]},{"given":"Zui","family":"Chen","sequence":"additional","affiliation":[{"name":"MIT CSAIL"}]},{"given":"Lei","family":"Cao","sequence":"additional","affiliation":[{"name":"University of Arizona\/MIT"}]},{"given":"Guoliang","family":"Li","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Samuel","family":"Madden","sequence":"additional","affiliation":[{"name":"MIT CSAIL"}]},{"given":"Xiaoyong","family":"Du","sequence":"additional","affiliation":[{"name":"Renmin University of China"}]},{"given":"Nan","family":"Tang","sequence":"additional","affiliation":[{"name":"HKUST (Guangzhou) \/ HKUST"}]}],"member":"320","published-online":{"date-parts":[[2024,8,30]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020","author":"Brown Tom B.","year":"2020","unstructured":"Tom B. 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In 13th Conference on Innovative Data Systems Research, CIDR 2023, Amsterdam, The Netherlands, January 8--11, 2023.www.cidrdb.org. https:\/\/www.cidrdb.org\/cidr2023\/papers\/p51-chen.pdf"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","unstructured":"Aakanksha Chowdhery Sharan Narang Jacob Devlin Maarten Bosma Gaurav Mishra Adam Roberts Paul Barham Hyung Won Chung Charles Sutton Sebastian Gehrmann Parker Schuh Kensen Shi Sasha Tsvyashchenko Joshua Maynez Abhishek Rao Parker Barnes Yi Tay Noam Shazeer Vinodkumar Prabhakaran Emily Reif Nan Du Ben Hutchinson Reiner Pope James Bradbury Jacob Austin Michael Isard Guy Gur-Ari Pengcheng Yin Toju Duke Anselm Levskaya Sanjay Ghemawat Sunipa Dev Henryk Michalewski Xavier Garcia Vedant Misra Kevin Robinson Liam Fedus Denny Zhou Daphne Ippolito David Luan Hyeontaek Lim Barret Zoph Alexander Spiridonov Ryan Sepassi David Dohan Shivani Agrawal Mark Omernick Andrew M. 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Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alch\u00e9-Buc, Emily B. Fox, and Roman Garnett (Eds.). 8024--8035. https:\/\/proceedings.neurips.cc\/paper\/2019\/hash\/bdbca288fee7f92f2bfa9f7012727740-Abstract.html"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"e_1_2_1_28_1","volume-title":"Proceedings of the 29th International Conference on Computational Linguistics, COLING 2022, Gyeongju, Republic of Korea, October 12--17","author":"Popescu Octavian","year":"2022","unstructured":"Octavian Popescu, Irene Manotas, Ngoc Phuoc An Vo, Hangu Yeo, Elahe Khorashani, and Vadim Sheinin. 2022. Addressing Limitations of Encoder-Decoder Based Approach to Text-to-SQL. 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Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault F\u00e9vry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, and Alexander M. Rush. 2022. Multitask Prompted Training Enables Zero-Shot Task Generalization. In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25--29, 2022. 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Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288 (2023)."},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514221.3517870"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3588938"},{"key":"e_1_2_1_43_1","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4--9, 2017, Long Beach, CA, USA, Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett (Eds.). 5998--6008. https:\/\/proceedings.neurips.cc\/paper\/2017\/hash\/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.677"},{"key":"e_1_2_1_45_1","volume-title":"The Tenth International Conference on Learning Representations, ICLR 2022","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le. 2022. Finetuned Language Models are Zero-Shot Learners. In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25--29, 2022. 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In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics Hong Kong China 1962--1979. 10.18653\/v1\/D19-1204","DOI":"10.18653\/v1\/D19-1204"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1425"},{"key":"e_1_2_1_49_1","volume-title":"Proceedings of the national conference on artificial intelligence. 1050--1055","author":"Zelle John M","year":"1996","unstructured":"John M Zelle and Raymond J Mooney. 1996. Learning to parse database queries using inductive logic programming. In Proceedings of the national conference on artificial intelligence. 1050--1055."},{"key":"e_1_2_1_50_1","unstructured":"Wayne Xin Zhao Kun Zhou Junyi Li Tianyi Tang Xiaolei Wang Yupeng Hou Yingqian Min Beichen Zhang Junjie Zhang Zican Dong Yifan Du Chen Yang Yushuo Chen Zhipeng Chen Jinhao Jiang Ruiyang Ren Yifan Li Xinyu Tang Zikang Liu Peiyu Liu Jian-Yun Nie and Ji-Rong Wen. 2023. A Survey of Large Language Models. arXiv:2303.18223 [cs.CL]"},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.558"},{"key":"e_1_2_1_52_1","volume-title":"On Robustness of Prompt-based Semantic Parsing with Large Pre-trained Language Model: An Empirical Study on Codex. arXiv preprint arXiv:2301.12868","author":"Zhuo Terry Yue","year":"2023","unstructured":"Terry Yue Zhuo, Zhuang Li, Yujin Huang, Yuan-Fang Li, Weiqing Wang, Gholamreza Haffari, and Fatemeh Shiri. 2023. 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