An LLM Maturity Model for Reliable and Transparent Text-to-Query
<|reference_start|>An LLM Maturity Model for Reliable and Transparent Text-to-Query: 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.<|reference_end|>
@article{yu2024an,
    title={An LLM Maturity Model for Reliable and Transparent Text-to-Query},
    author={Lei Yu (Expression) and Abir Ray (Expression)},
    journal={arXiv preprint arXiv:2402.14855},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.14855},
    primaryClass={cs.CL cs.AI}
}