Year: 2025
Type: preprint
Abstract: This paper presents the design, implementation, and evaluation behind a Large Language Model (LLM) agent that chats with an industrial production-grade ERP system. The agent is capable of interpreting natural language queries and translating them into executable SQL statements, leveraging open-weight LLMs. A novel dual-agent architecture combining reasoning and critique stages was proposed to improve query generation reliability.
Source: arXiv (Cornell University)
Authors: Gómez, Jorge Ruiz, Susinos, Lidia Andrés, Olivé, Jorge Alamo, Osorno, Sonia Rey, Hernández, Manuel Luis Gonzalez
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4414920616
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