标题： QueryGenie：使基于LLM的数据库查询透明且可控 显示英文标题

标题： QueryGenie: Making LLM-Based Database Querying Transparent and Controllable

摘要： 基于大型语言模型（LLMs）的对话式用户界面显著降低了数据库查询的技术门槛。 然而，现有工具仍然面临多个挑战，例如对用户意图的误解、生成幻觉内容以及缺乏有效的人类反馈机制——所有这些问题都削弱了它们的可靠性与实用性。 为了解决这些问题并促进更透明和可控的查询体验，我们提出了QueryGenie，一个交互式系统，使用户能够监控、理解和引导由LLM驱动的查询生成过程。 通过逐步推理、实时验证和响应式交互机制，用户可以迭代地优化查询逻辑并确保与他们的意图一致。 显示英文摘要

摘要： Conversational user interfaces powered by large language models (LLMs) have significantly lowered the technical barriers to database querying. However, existing tools still encounter several challenges, such as misinterpretation of user intent, generation of hallucinated content, and the absence of effective mechanisms for human feedback-all of which undermine their reliability and practical utility. To address these issues and promote a more transparent and controllable querying experience, we proposed QueryGenie, an interactive system that enables users to monitor, understand, and guide the LLM-driven query generation process. Through incremental reasoning, real-time validation, and responsive interaction mechanisms, users can iteratively refine query logic and ensure alignment with their intent.