Results 91 to 100 of about 9,267 (223)

End-to-End Cross-Domain Text-to-SQL Semantic Parsing with Auxiliary Task [PDF]

, 2021
Peng Shi, Tao Yu, Patrick Ng, Zhiguo Wang   +3 more
openalex   +1 more source

SQL-PaLM: Improved Large Language ModelAdaptation for Text-to-SQL

, 2023
One impressive emergent capability of large language models (LLMs) is generation of code, including Structured Query Language (SQL) for databases. For the task of converting natural language text to SQL queries, Text-to-SQL, adaptation of LLMs is of ...
Arik, Sercan O, Dai, Hanjun, Nakhost, Hootan, Pfister, Tomas, Sinha, Rajarishi, Sun, Ruoxi, Yin, Pengcheng   +6 more
core  

Brain‐peripheral proteome crosstalk in Alzheimer's disease with and without diabetes mellitus

Alzheimer's &Dementia, Volume 22, Issue 1, January 2026.
Abstract BACKGROUND Although considerable research has investigated diabetes mellitus (DM) as a risk factor for Alzheimer's disease (AD) dementia, the mechanistic understanding of the associations between peripheral and central biological processes in AD and AD within DM remains limited.
Anat Yaskolka Meir, Xingyan Wang, Shinya Tasaki, Vishal Sarsani, Aron S. Buchman, Steven E. Arnold, David A. Bennett, Vladislav A. Petyuk, Liming Liang, Ana W. Capuano, Zoe Arvanitakis   +10 more
wiley   +1 more source

DKASQL: Dynamic Knowledge Adaptation for Domain-Specific Text-to-SQL

Applied Sciences
Text2SQL aims to translate natural language queries into structured query language (SQL). LLM-based Text2SQL methods have gradually become mainstream because of their strong capabilities in language understanding and transformation.
Huaxing Bian, Guanrong Li, Yifan Wang, Qinghan Fu, Jian Shen, Xixian Yao, Zhen Wu   +6 more
doaj   +1 more source

FAIR Workflows in Earth System Modelling: A Use Case With Semantic Data Management

Geoscience Data Journal, Volume 13, Issue 1, January 2026.
We present a semantic research data management workflow that enables the re‐use of legacy simulation datasets in accordance with FAIR principles. The approach integrates automated semantic annotation, queryable data access, and a connected JupyterHub for FAIR‐compliant output analysis and storage of derived results. ABSTRACT The amount of research data
Sinikka T. Lennartz, Alexander Schlemmer
wiley   +1 more source

Leveraging Large Language Model for Enhanced Text-to-SQL Parsing

IEEE Access
Text-to-SQL conversion, the process of generating SQL queries from natural language input, has gained significant attention due to its potential to simplify database interaction. Although benchmarks in this task have driven advancements in the field, the
Zecheng Zhan, E. Haihong, Meina Song
doaj   +1 more source

Text to SQL Query

International Journal for Research in Applied Science and Engineering Technology
With the exponential growth of data in modern organizations, the ability to extract meaningful insights from databases has become crucial. However, interacting with structured databases often requires knowledge of SQL (Structured Query Language), which presents a barrier for non-technical users.
openaire   +1 more source

Ar-Spider: Text-to-SQL in Arabic

Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing
Comment: ACM SAC Conference (SAC 24)
Saleh Almohaimeed, Saad Almohaimeed, Mansour Al Ghanim, Liqiang Wang   +3 more
openaire   +2 more sources

Data Ambiguity Strikes Back: How Documentation Improves GPT's Text-to-SQL

, 2023
Text-to-SQL allows experts to use databases without in-depth knowledge of them. However, real-world tasks have both query and data ambiguities. Most works on Text-to-SQL focused on query ambiguities and designed chat interfaces for experts to provide ...
Damalapati, Pavan Kalyan, Huang, Zezhou, Wu, Eugene   +2 more
core  

Automating Algorithm Experiments With ALGator: From Problem Modeling to Reproducible Results

Software: Practice and Experience, Volume 56, Issue 1, Page 26-41, January 2026.
ABSTRACT Background Theoretical algorithm analysis provides fundamental insights into algorithm complexity but relies on simplified and often outdated computational models. Experimental algorithmics complements this approach by evaluating the empirical performance of algorithm implementations on real data and modern computing platforms.
Tomaž Dobravec
wiley   +1 more source