Demystifying structured data: How to speak an LLM’s native language

Elk Marketing reports that structured data enhances AI understanding, enabling accurate entity recognition and improved ...
EurekAlert!

A cost-effective text-to-SQL approach based on adaptive refinement

The purpose of the Text-to-SQL task is to bridge the gap between natural language and SQL queries. Current approaches mainly rely on large language models (LLMs), but employing them for Text-to-SQL ha ...
Analytics Insight

Best Data Analysis Courses in 2026: What to Learn First and Where to Learn It

In-demand skills include data analysis. It has been predicted that in 2026 businesses will place a high value on analysts who can extract relevant details and i ...

Smart Last-Minute Tips to Crack CBSE Class 12 Computer Science Exam

Experts advise focusing on Python, MySQL, and Networking, practicing output questions, mastering SQL basics, revising key ...
IEEE

IRAM-SQL: A Language Model Integrating Relation-Aware Mechanism for Text-to-SQL

Abstract: The task of text-to-SQL aims to convert natural language questions into executable SQL queries within relational databases. This greatly enhances the usability of relational database ...
IEEE

AquaVLM: A Domain-Specific Vision–Language Model for Structured Understanding of Oceanarium Scenes

Abstract: Vision-Language Models (VLMs) have advanced cross-modal understanding and generation, yet their domain adaptability remains limited. To address the lack of high-quality captions for fish ...
GitHub

SQLBarber: Leverageing Large Language Models Generate Customized and Realistic SQL Workloads (SIGMOD 2026)

Database research and development often require a large number of SQL queries for benchmarking purposes. However, acquiring real-world SQL queries is challenging due to privacy concerns, and existing ...