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Robust Text-to-SQL via Feature Augmentation by manoj523 is a document available to read on EtoBox.

What is Robust Text-to-SQL via Feature Augmentation about?

The paper presents a novel Sequential Feature Augmentation Method (SFAM) aimed at enhancing the robustness and accuracy of Text-to-SQL models, which convert natural language queries into SQL. SFAM employs a sequential feature augmentation approach during the text encoding stage, utilizing sequential consistency learning and mutual information maximization to improve model performance. Experimental results demonstrate that SFAM outperforms existing state-of-the-art methods on a dataset derived from the marke

Author

manoj523

Language

EN