NL2SQL Task

The NL2SQL task focuses on automatically translating natural language questions into executable SQL queries, enabling seamless interaction with databases using human-friendly language. Current research emphasizes improving the accuracy and efficiency of this translation, exploring techniques like in-context learning with carefully selected demonstration examples, multi-task learning architectures that decompose the problem into sub-tasks, and hybrid approaches combining the strengths of different large language models (LLMs) and pre-trained language models (PLMs). This field is significant for its potential to democratize access to data analysis and improve efficiency in various domains, from healthcare (e.g., querying electronic health records) to business intelligence.