87 citations · 133 across the 7 of their papers we have counts for
7 papers
Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs
Jinyang Li, Binyuan Hui, Ge Qu +15
Text-to-SQL parsing, which aims at converting natural language instructions into executable SQLs, has gained increasing attention in recent years. In particular, Codex and ChatGPT…
Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing
Jinyang Li, Binyuan Hui, Reynold Cheng +7
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, as it can assis…
SUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers
Bowen Qin, Lihan Wang, Binyuan Hui +7
This paper aims to improve the performance of text-to-SQL parsing by exploring the intrinsic uncertainties in the neural network based approaches (called SUN). From the data uncert…
A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions
Bowen Qin, Binyuan Hui, Lihan Wang +9
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 langu…
Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing
Lihan Wang, Bowen Qin, Binyuan Hui +7
The importance of building text-to-SQL parsers which can be applied to new databases has long been acknowledged, and a critical step to achieve this goal is schema linking, i.e., p…
SSQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parsers
Binyuan Hui, Ruiying Geng, Lihan Wang +4
The task of converting a natural language question into an executable SQL query, known as text-to-SQL, is an important branch of semantic parsing. The state-of-the-art graph-based…
Linking-Enhanced Pre-Training for Table Semantic Parsing
Bowen Qin, Lihan Wang, Binyuan Hui +5
Recently pre-training models have significantly improved the performance of various NLP tasks by leveraging large-scale text corpora to improve the contextual representation abilit…