Abstract: General Text-to-3D (GT23D) generation is crucial for creating diverse 3D content across objects and scenes, yet it faces two key challenges: 1) ensuring semantic consistency between input ...

Abstract: Complex Text-to-SQL generation remains challenging due to the lack of explicit modeling of hierarchical schema structures and persistent semantic mismatches between natural-language queries ...

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 ...

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 ...

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, ...

There is a responses agent in semantic_kernel.agents but I not an equivalent to AzureChatCompletion in semantic_kernel.connectors.ai.open_ai. This means I can't create a service for the Kernel, so are ...

Search engines have come a long way from relying on exact match keywords. Today, they try to understand the meaning behind content — what it says, how it says it, and whether it truly answers the ...