Closed ct-source closed 10 months ago
Hi, the prevalence of lengthy DDL inputs is a common occurrence in real-world applications. To address this issue, an effective approach involves implementing a preprocessing module that extracts the most relevant tables and columns based on the natural language questions. This technique could significantly reduce the overall length of the input sequence, leading to improved efficiency.
For further insight, you can explore our recent work, CodeS. In this work, we have successfully integrated a schema item filter, which plays a pivotal role in attaining the aforementioned objective. 😉
Hi, the prevalence of lengthy DDL inputs is a common occurrence in real-world applications. To address this issue, an effective approach involves implementing a preprocessing module that extracts the most relevant tables and columns based on the natural language questions. This technique could significantly reduce the overall length of the input sequence, leading to improved efficiency.
For further insight, you can explore our recent work, CodeS. In this work, we have successfully integrated a schema item filter, which plays a pivotal role in attaining the aforementioned objective. 😉
the Link you offer is closed!
Hi, the prevalence of lengthy DDL inputs is a common occurrence in real-world applications. To address this issue, an effective approach involves implementing a preprocessing module that extracts the most relevant tables and columns based on the natural language questions. This technique could significantly reduce the overall length of the input sequence, leading to improved efficiency. For further insight, you can explore our recent work, CodeS. In this work, we have successfully integrated a schema item filter, which plays a pivotal role in attaining the aforementioned objective. 😉
the Link you offer is closed!
I found code here. https://github.com/defog-ai/sql-eval/blob/main/utils/pruning.py
This issue is stale because it has been open for 30 days with no activity.
This issue was closed because it has been inactive for 14 days since being marked as stale.
Thank you for your awlsome work!