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 ...

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 this tutorial, we build an advanced AI agent using Semantic Kernel combined with Google’s Gemini free model, and we run it seamlessly on Google Colab. We start by wiring Semantic Kernel plugins as ...

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 ...

Snowflake has thousands of enterprise customers who use the company's data and AI technologies. Though many issues with generative AI are solved, there is still lots of room for improvement. Two such ...

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 ...

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI company, announced the availability of its hybrid search capabilities for Microsoft’s Semantic Kernel project, making Elastic’s ...

This project demonstrates a two-step agent flow using Azure OpenAI's ChatCompletions API. It features a researcher agent that gathers information on a given topic and a writer agent that synthesizes ...