Introduction Modern applications are increasingly powered by large language models (LLMs) that don’t just generate text—they can call live APIs, query databases, and even trigger automated workflows.

"I’ve developed a text-to-SQL application using Gemini, which converts natural language input into SQL queries. By leveraging the power of Gemini, the application efficiently understands and processes ...

Abstract: Text-to-SQL conversion, the process of generating SQL queries from natural language input, has gained significant attention due to its potential to simplify database interaction. Although ...

"App Orchid's groundbreaking milestone in text-to-SQL accuracy is a ... The Spider dataset is a benchmark comprising over 10,000 natural language questions mapped to SQL queries across 200 ...

AtScale launches public leaderboard for Text-to-SQL, offering a standardized framework to enhance transparency, competition & collaboration in T2SQL.

Figure 1. Complex query match rate over training epochs. As can be seen in Figure 1, our method (Ours) performs well in the match rate of complex queries, and the match rate continues to increase as ...

The Text-to-SQL task has significant application prospects in automating relational database query interfaces. It can reduce user learning costs and improve data query efficiency. However, in ...

For instance, existing text-to-SQL methods — that convert a text prompt into a SQL query that could be executed by databases — focus only on natural language questions that can be expressed in ...

In conclusion, MAG-SQL addresses the critical challenges of translating natural language into SQL commands. By utilizing a multi-agent framework and focusing on iterative refinement, MAG-SQL offers a ...