Gar $$\scriptstyle ++$$: Natural Language to SQL Translation with Efficient Generate-and-Rank
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-7238-4_26
Reference57 articles.
1. Fan, Y., et al.: GAR: a generate-and-rank approach for natural language to SQL translation. In: Proceedings of the 39th International Conference on Data Engineering, pp. 110–122 (2023)
2. Fan, Y., Ren, T., He, Z., Wang, X., Zhang, Y., Li, X.: GenSQL: a generative natural language interface to database systems. In: Proceedings of the 39th International Conference on Data Engineering, pp. 3603–3606 (2023)
3. Bogin, B., Berant, J., Gardner, M.: Representing schema structure with graph neural networks for text-to-SQL parsing. In: Association for Computational Linguistics, pp. 4560–4565 (2019)
4. Guo, J., et al.: Towards complex text-to-SQL in cross-domain database with intermediate representation. In: Association for Computational Linguistics, pp. 4524–4535 (2019)
5. Wang, B., Shin, R., Liu, X., Polozov, O., Richardson, M.: RAT-SQL: relation-aware schema encoding and linking for text-to-SQL parsers. In: Association for Computational Linguistics, pp. 7567–7578 (2020)
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