Results 121 to 130 of about 9,267 (223)

OPTIC—OPtimized Translation and Interaction for Cloud-Costs: Use of FOCUS Standardization and LLM Integration for Cloud Billing Analysis

IEEE Access
Managing billing data across multicloud environments remains a significant challenge due to heterogeneous data formats, fragmented cost metrics, and the technical complexity of cost analysis.
Gilberto N. Junior, Cesar Marcon
doaj   +1 more source

Comparing Data Store Performance for Full-Text Search: To SQL or to NoSQL?

, 2023
George Fotopoulos, Paris Koloveas, Paraskevi Raftopoulou, Christos Tryfonopoulos   +3 more
openalex   +1 more source

$R^3$: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent System for Text-to-SQL Tasks

Large Language Models (LLMs) have demonstrated strong performance on various tasks. To unleash their power on the Text-to-SQL task, we propose $R^3$ (Review-Rebuttal-Revision), a consensus-based multi-agent system for Text-to-SQL tasks. $R^3$ outperforms
Deng, Naihao, Jiang, Feng, Mihalcea, Rada, Wang, Cunxiang, Xia, Hanchen, Zhang, Yue, Zhao, Guojiang   +6 more
core  

Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies [PDF]

Association for Computational Linguistics 2025, Chandarana, Yash Kaushikbhai, Gupta, Chirag, Liu, Terrance, Preotiuc-Pietro, Daniel, Wang, Shuyi   +5 more
openalex   +2 more sources

RGISQL: Integrating Refined Grammatical Information into Relational Graph Neural Network for Text-to-SQL Task

Applied Sciences
The text-to-SQL task aims to convert natural language questions into corresponding SQL queries based on a given database schema. Previous models that rely on graph neural networks often struggle to accurately capture the complex grammatical relationships
Shuiyan Li, Yaozhen He, Longhao Ao, Rongzhi Qi   +3 more
doaj   +1 more source

Exploring the Compositional Generalization in Context Dependent Text-to-SQL Parsing [PDF]

, 2023
Aiwei Liu, Wei Liu, Xuming Hu, Shuang Li, Fukun Ma, Yawen Yang, Lijie Wen   +6 more
openalex   +1 more source

Deep Learning Driven Natural Languages Text to SQL Query Conversion: A Survey [PDF]

, 2022
Ayush Kumar, Parth Nagarkar, Prabhav Nalhe, S. Vijayakumar   +3 more
openalex   +1 more source

DAC: Decomposed Automation Correction for Text-to-SQL

Findings of the Association for Computational Linguistics: EMNLP 2025
Text-to-SQL is an important task that helps people obtain information from databases by automatically generating SQL queries. Considering the brilliant performance, approaches based on Large Language Models (LLMs) become the mainstream for text-to-SQL.
Wang, Dingzirui, Dou, Longxu, Zhang, Xuanliang, Zhu, Qingfu, Che, Wanxiang   +4 more
openaire   +2 more sources

Schema Retrieval with Embeddings and Vector Stores Using Retrieval-Augmented Generation and LLM-Based SQL Query Generation

Applied Sciences
In today’s world, where the volume and variety of data are increasing at an extraordinary rate, extracting meaningful insights from data is of critical importance; however, the complexity of standard database query languages makes it difficult for users ...
Mehmet Bozdemir, Metin Bilgin
doaj   +1 more source

Self-correcting complex semantic analysis method based on pre-training mechanism

Tongxin xuebao, 2019
In the process of knowledge service,in order to meet the fragmentation management needs of intellectualization,knowledge ability,refinement and reorganization content resources.Through deep analysis and mining of semantic hidden knowledge,technology ...
Qing LI, Jiang ZHONG, Lili LI, Qi LI
doaj   +2 more sources