Recent advances in text-to-SQL: a survey of what we have and what we expect
Text-to-SQL has attracted attention from both the natural language processing and database
communities because of its ability to convert the semantics in natural language into SQL …
communities because of its ability to convert the semantics in natural language into SQL …
Learning contextual representations for semantic parsing with generation-augmented pre-training
Most recently, there has been significant interest in learning contextual representations for
various NLP tasks, by leveraging large scale text corpora to train powerful language models …
various NLP tasks, by leveraging large scale text corpora to train powerful language models …
Sadga: Structure-aware dual graph aggregation network for text-to-sql
The Text-to-SQL task, aiming to translate the natural language of the questions into SQL
queries, has drawn much attention recently. One of the most challenging problems of Text-to …
queries, has drawn much attention recently. One of the most challenging problems of Text-to …
NL-EDIT: Correcting semantic parse errors through natural language interaction
We study semantic parsing in an interactive setting in which users correct errors with natural
language feedback. We present NL-EDIT, a model for interpreting natural language …
language feedback. We present NL-EDIT, a model for interpreting natural language …
Towards robustness of text-to-SQL models against natural and realistic adversarial table perturbation
The robustness of Text-to-SQL parsers against adversarial perturbations plays a crucial role
in delivering highly reliable applications. Previous studies along this line primarily focused …
in delivering highly reliable applications. Previous studies along this line primarily focused …
Mt-teql: evaluating and augmenting neural nlidb on real-world linguistic and schema variations
Natural Language Interface to Database (NLIDB) translates human utterances into SQL
queries and enables database interactions for non-expert users. Recently, neural network …
queries and enables database interactions for non-expert users. Recently, neural network …
Trojansql: Sql injection against natural language interface to database
The technology of text-to-SQL has significantly enhanced the efficiency of accessing and
manipulating databases. However, limited research has been conducted to study its …
manipulating databases. However, limited research has been conducted to study its …
Benchmarking and improving text-to-sql generation under ambiguity
Research in Text-to-SQL conversion has been largely benchmarked against datasets where
each text query corresponds to one correct SQL. However, natural language queries over …
each text query corresponds to one correct SQL. However, natural language queries over …
Non-programmers can label programs indirectly via active examples: A case study with text-to-SQL
Can non-programmers annotate natural language utterances with complex programs that
represent their meaning? We introduce APEL, a framework in which non-programmers …
represent their meaning? We introduce APEL, a framework in which non-programmers …
ConDA: state-based data augmentation for context-dependent text-to-SQL
The context-dependent text-to-SQL task has profound real-world implications, as it facilitates
users in extracting knowledge from vast databases, which allows users to acquire the …
users in extracting knowledge from vast databases, which allows users to acquire the …