A survey on text-to-sql parsing: Concepts, methods, and future directions
Text-to-SQL parsing is an essential and challenging task. The goal of text-to-SQL parsing is
to convert a natural language (NL) question to its corresponding structured query language …
to convert a natural language (NL) question to its corresponding structured query language …
Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls
Text-to-SQL parsing, which aims at converting natural language instructions into executable
SQLs, has gained increasing attention in recent years. In particular, GPT-4 and Claude-2 …
SQLs, has gained increasing attention in recent years. In particular, GPT-4 and Claude-2 …
Resdsql: Decoupling schema linking and skeleton parsing for text-to-sql
One of the recent best attempts at Text-to-SQL is the pre-trained language model. Due to the
structural property of the SQL queries, the seq2seq model takes the responsibility of parsing …
structural property of the SQL queries, the seq2seq model takes the responsibility of parsing …
TaBERT: Pretraining for joint understanding of textual and tabular data
Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-
based natural language (NL) understanding tasks. Such models are typically trained on free …
based natural language (NL) understanding tasks. Such models are typically trained on free …
A survey on deep learning approaches for text-to-SQL
G Katsogiannis-Meimarakis, G Koutrika - The VLDB Journal, 2023 - Springer
To bridge the gap between users and data, numerous text-to-SQL systems have been
developed that allow users to pose natural language questions over relational databases …
developed that allow users to pose natural language questions over relational databases …
Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task
We present Spider, a large-scale, complex and cross-domain semantic parsing and text-to-
SQL dataset annotated by 11 college students. It consists of 10,181 questions and 5,693 …
SQL dataset annotated by 11 college students. It consists of 10,181 questions and 5,693 …
Graphix-t5: Mixing pre-trained transformers with graph-aware layers for text-to-sql parsing
The task of text-to-SQL parsing, which aims at converting natural language questions into
executable SQL queries, has garnered increasing attention in recent years. One of the major …
executable SQL queries, has garnered increasing attention in recent years. One of the major …
The natural language decathlon: Multitask learning as question answering
Deep learning has improved performance on many natural language processing (NLP)
tasks individually. However, general NLP models cannot emerge within a paradigm that …
tasks individually. However, general NLP models cannot emerge within a paradigm that …
Towards complex text-to-sql in cross-domain database with intermediate representation
We present a neural approach called IRNet for complex and cross-domain Text-to-SQL.
IRNet aims to address two challenges: 1) the mismatch between intents expressed in natural …
IRNet aims to address two challenges: 1) the mismatch between intents expressed in natural …
A survey on table question answering: recent advances
Abstract Table Question Answering (Table QA) refers to providing precise answers from
tables to answer a user's question. In recent years, there have been a lot of works on table …
tables to answer a user's question. In recent years, there have been a lot of works on table …