Large language models (LLMs) have exhibited an emergent in-context learn...
Table-based reasoning has shown remarkable progress in combining deep mo...
Text-to-SQL parsing tackles the problem of mapping natural language ques...
In this paper, we propose a novel SQL guided pre-training framework STAR...
Most graph-to-text works are built on the encoder-decoder framework with...
This paper aims to improve the performance of text-to-SQL parsing by
exp...
Text-to-SQL parsing is an essential and challenging task. The goal of
te...
The importance of building text-to-SQL parsers which can be applied to n...
Text-to-SQL aims to map natural language questions to SQL queries. The
s...
Semantic parsing has long been a fundamental problem in natural language...
This paper proposes Dynamic Memory Induction Networks (DMIN) for few-sho...
Text classification tends to struggle when data is deficient or when it ...