An LLM Maturity Model for Reliable and Transparent Text-to-Query

• URL: http://arxiv.org/abs/2402.14855v1
• Date: Tue, 20 Feb 2024 06:20:09 GMT
• Title: An LLM Maturity Model for Reliable and Transparent Text-to-Query
• Authors: Lei Yu (Expression) and Abir Ray (Expression)
• Abstract summary: This work proposes an LLM maturity model tailored for text-to-query applications. This maturity model seeks to fill the existing void in evaluating LLMs in such applications by incorporating dimensions beyond mere correctness or accuracy.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Recognizing the imperative to address the reliability and transparency issues of Large Language Models (LLM), this work proposes an LLM maturity model tailored for text-to-query applications. This maturity model seeks to fill the existing void in evaluating LLMs in such applications by incorporating dimensions beyond mere correctness or accuracy. Moreover, this work introduces a real-world use case from the law enforcement domain and showcases QueryIQ, an LLM-powered, domain-specific text-to-query assistant to expedite user workflows and reveal hidden relationship in data.

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