… seq-to-seq model to robust text-to-SQL generation. Instead of inducing constraint to decoder
… model with Schema-aware Denoising (SeaD), which consists of two denoising objectives …

… Instead of formulating the task of text-to-SQL as slot-filling, we propose to train sequence-to-sequence
model with Schemaaware Denoising (SeaD), which consists of two denoising …

… SEAD [90] is an end-to-end Textto-SQL generation method that employs more sophisticated
… Dong, “Sead: End-to-end text-to-sql generation with schema-aware denoising,” 2023. […

… The results are consistent with our motivation to tackle complex text-to-SQL and verify
that … novel schema-aware Multi-Task learning framework called MTSQL for complex text-to-SQL. …

… text-to-SQL task is to convert natural language queries into SQL queries However, the
presence of extensive text-to-SQL … issue and enhance performance in text-to-SQL tasks. These …

… (1) We conduct a comprehensive investigation into the reliability of Text-to-SQL generation,
identifying key challenges and opportunities for improvement. (2) We propose a novel …

… prone to ambiguities, complicating the text to SQL generation process and the evaluation of
… to prominence in text-to-SQL parsing largely because they can be trained end-to-end, thus …

… In our evaluation of text-to-SQL models, we utilized exact set match accuracy and execution
accuracy. The former involves comparing the components of SQL queries, such as select, …

… parsing mainly because they can be trained in an end-to-end way and reduce the need for
… Dong, “Sead: End-to-end text-to-sql generation with schemaaware denoising,” ArXiv preprint…

… Text-to-SQL is crafted to convert natural language questions into executable SQL queries,
creating a user-friendly interface for relational databases that enhances both usability and …