SQLucid：通过交互式解释为自然语言数据库查询奠定基础
SQLucid: Grounding Natural Language Database Queries with Interactive Explanations
AI总结：
本文提出 SQLucid 交互式界面，通过视觉对应、中间结果和可编辑的自然语言分步 SQL 解释，帮助非专家理解并优化查询，实验证明其提升了任务准确性与用户信心。
摘要：
尽管机器学习的最新进展显著提升了数据库自然语言接口的性能，但这些系统的准确性和可靠性仍然有限，在高风险领域尤为突出。本文提出 SQLucid，这是一种新颖的用户界面，旨在弥合非专家用户与复杂数据库查询过程之间的鸿沟。SQLucid 通过整合视觉对应关系、中间查询结果，以及用自然语言呈现且可编辑的逐步 SQL 解释来解决现有局限，从而促进用户理解和参与。这种独特的功能组合使用户能够轻松且精确地理解并优化 SQL 查询。研究开展了两项用户研究和一项定量实验以验证 SQLucid 的有效性；结果表明，与现有接口相比，其在任务完成准确性和用户信心方面均有显著提升。代码可在 https://github.com/magic-YuanTian/SQLucid 获取。
英文摘要：
Though recent advances in machine learning have led to significant improvements in natural language interfaces for databases, the accuracy and reliability of these systems remain limited, especially in high-stakes domains. This paper introduces SQLucid, a novel user interface that bridges the gap between non-expert users and complex database querying processes. SQLucid addresses existing limitations by integrating visual correspondence, intermediate query results, and editable step-by-step SQL explanations in natural language to facilitate user understanding and engagement. This unique blend of features empowers users to understand and refine SQL queries easily and precisely. Two user studies and one quantitative experiment were conducted to validate SQLucid's effectiveness, showing significant improvement in task completion accuracy and user confidence compared to existing interfaces. Our code is available at https://github.com/magic-YuanTian/SQLucid.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
