Results 171 to 180 of about 73,684 (223)

CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL

International Conference on Learning Representations
In tackling the challenges of large language model (LLM) performance for Text-to-SQL tasks, we introduce CHASE-SQL, a new framework that employs innovative strategies, using test-time compute in multi-agent modeling to improve candidate generation and ...
Mohammadreza Pourreza, Hailong Li, Ruoxi Sun, Yeounoh Chung, Shayan Talaei, Gaurav Tarlok Kakkar, Yu Gan, Amin Saberi, Fatma Ozcan, Sercan Ö. Arik   +9 more
semanticscholar   +1 more source

Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search

International Conference on Machine Learning
Text-to-SQL, which enables natural language interaction with databases, serves as a pivotal method across diverse industries. With new, more powerful large language models (LLMs) emerging every few months, fine-tuning has become incredibly costly, labor ...
Boyan Li, Jiayi Zhang, Ju Fan, Yanwei Xu, Chong Chen, Nan Tang, Yuyu Luo   +6 more
semanticscholar   +1 more source

SQL

Proceedings of the 47th ACM Technical Symposium on Computing Science Education, 2016
The Structured Query Language (SQL) is the main programing language designed to manage data stored in database systems. While SQL was initially used only with relational database management systems (RDBMS), its use has been significantly extended with the advent of new types of database systems.
Yasin N. Silva, Isadora Almeida, Michell Queiroz   +2 more
openaire   +2 more sources

MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation

International Conference on Computational Linguistics
Recent advancements in large language models (LLMs) have enabled in-context learning (ICL)-based methods that significantly outperform fine-tuning approaches for text-to-SQL tasks. However, their performance is still considerably lower than that of human
Dongjun Lee, Choongwon Park, Jaehyuk Kim, Heesoo Park   +3 more
semanticscholar   +1 more source

PL/SQL from SQL

2011
Functions are an integral part of any well-designed PL/SQL application. They are an embodiment of programming best practices, such as code modularization, reuse, and the encapsulation of business or application logic. When used as simple building-blocks for larger programs, they can be an elegant and simple way to extend functionality while reducing ...
openaire   +1 more source

A Survey on Employing Large Language Models for Text-to-SQL Tasks

ACM Computing Surveys
With the development of the Large Language Models (LLMs), a large range of LLM-based Text-to-SQL(Text2SQL) methods have emerged. This survey provides a comprehensive review of LLM-based Text2SQL studies.
Liang Shi, Zhengju Tang, Nan Zhang, Xiaotong Zhang, Zhi Yang   +4 more
semanticscholar   +1 more source

SQL

2017
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  +5 more sources

Synthesizing Text-to-SQL Data from Weak and Strong LLMs

Annual Meeting of the Association for Computational Linguistics
The capability gap between open-source and closed-source large language models (LLMs) remains a challenge in text-to-SQL tasks. In this paper, we introduce a synthetic data approach that combines data produced by larger, more powerful models (strong ...
Jiaxi Yang, Binyuan Hui, Min Yang, Jian Yang, Junyang Lin, Chang Zhou   +5 more
semanticscholar   +1 more source

Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generation

Annual Meeting of the Association for Computational Linguistics
Large Language Models (LLMs) driven by In-Context Learning (ICL) have significantly improved the performance of text-to-SQL. Previous methods generally employ a two-stage reasoning framework, namely 1) schema linking and 2) logical synthesis, making the ...
Ge Qu, Jinyang Li, Bowen Li, Bowen Qin, Nan Huo, Chenhao Ma, Reynold Cheng   +6 more
semanticscholar   +1 more source

The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models

arXiv.org
Schema linking is a crucial step in Text-to-SQL pipelines. Its goal is to retrieve the relevant tables and columns of a target database for a user's query while disregarding irrelevant ones.
Karime Maamari, Fadhil Abubaker, Daniel Jaroslawicz, Amine Mhedhbi   +3 more
semanticscholar   +1 more source