SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 Isaque Oliveira do Nascimento(isaque.nascimento@usp.br)
2 Kelly Braghetto(kellyrb@ime.usp.br)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 Cai, Q., Liang, H., Xu, C., Xie, T., Zhang, W., and Cui, B. (2025). Text2sql-flow: A robust sql-aware data augmentation framework for text-to-sql. arXiv:2511.10192.
2 Gan, Y., Chen, X., Huang, Q., Purver, M., Woodward, J. R., Xie, J., and Huang, P. (2021). Towards robustness of text-to-sql models against synonym substitution. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and 11th International Joint Conference on Natural Language Processing, pages 2505–2515.
3 Katsogiannis-Meimarakis, G. and Koutrika, G. (2023). A survey on deep learning approaches for text-to-SQL. The VLDB Journal, 32(4):905–936.
4 Liu, S., Almohaimeed, S., and Wang, L. (2024). Reformer: A chatgpt-driven data synthesis framework elevating text-to-sql models. In 2024 International Conference on Machine Learning and Applications (ICMLA), page 828–833. IEEE.
5 Liu, X., Shen, S., Li, B., Ma, P., Jiang, R., Zhang, Y., Fan, J., Li, G., Tang, N., and Luo, Y. (2025). A survey of text-to-sql in the era of llms: Where are we, and where are we going? IEEE Transactions on Knowledge and Data Engineering.
6 Lopes, D. O. and Braghetto, K. R. (2026). AtlasSQL-BR. https://huggingface.co/datasets/datafromlopes/atlas-sql-br. Accessed: 2026-05-18.
7 Mao, T. (2023). Sqlglot documentation. https://sqlglot.com/sqlglot.html. Accessed: 2026-05-18.
8 Shorten, C., Khoshgoftaar, T. M., and Furht, B. (2021). Text data augmentation for deep learning. Journal of Big Data, 8(1):101.
9 Zhu, Y., Si, J., Zhao, Y., Zhu, H., Zhou, D., and He, Y. (2023). Explain, edit, generate: rationale-sensitive counterfactual data augmentation for multi-hop fact verification. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 13377–13392.