Papers by Zhihui Shao
Enhancing Text-to-SQL with Question Classification and Multi-Agent Collaboration (2025.findings-naacl)
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| Challenge: | Existing research focuses on the optimization of prompts and improvements in workflow, with few studies delving into the exploration of the questions. |
| Approach: | They propose a text-to-SQL framework based on question classification and multi-agent collaboration (QCMA-Sql) they employ multiple cross-attention mechanisms to train a schema selector to classify questions and select the most suitable database schema. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on the Spider dataset and achieves 87.4% execution accuracy. |