Enterprises seeking to make good on the promise of agentic AI will need a platform for building, wrangling, and monitoring AI agents in purposeful workflows. In this quickly evolving space, myriad ...

Abstract: Querying relational databases through natural language remains a difficult task, especially for users without knowledge of SQL. Existing Text-to-SQL approaches often face issues of semantic ...

Spider is a large human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task (natural language interfaces for relational databases). It is released along with our EMNLP ...

Every data engineering team right now is being asked the same question: "How do we build a chatbot that talks to our data?" The prototypes are deceptively simple. A developer connects GPT-5.1 to a ...

Abstract: Current Text-to-SQL methods are evaluated and only focused on executable queries overlooking the semantic alignment challenge both in terms of the semantic meaning of the query and the ...

A team of AI researchers at Bloomberg have developed PExA, an agentic framework that achieved 70.2% execution accuracy, sharing one of the top positions on the Spider 2.0 (Snow) leaderboard, one of ...

In most enterprises, data access still feels like a locked room with SQL as the only key. Business teams depend on data engineers for every report, dashboard, or metric tweak. Even in the age of ...

Semantic SEO helps search engines understand context. Learn how to use entities, topics, and intent to build richer content that ranks higher. Semantic SEO aims to describe the relationships between ...

Discover how Tinker and Ray are utilized to fine-tune text-to-SQL models, enhancing AI capabilities in generating efficient SQL queries. In an innovative approach to advancing text-to-SQL models, ...