Track-SQL: Enhancing Generative Language Models with Dual-Extractive Modules for Schema and Context Tracking in Multi-turn Text-to-SQL
Track-SQL: 通过双提取模块增强生成语言模型以在多轮文本到SQL中进行模式和上下文跟踪
机构 * School of Computer Science, Guangdong University of Technology（广东技术大学计算机科学学院） ； Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)（广东人工智能与数字经济实验室） ； Peng Cheng Laboratory（鹏城实验室） ； College of Science, Shantou University（汕头大学理学院）
AI总结 Track-SQL通过双提取模块提升生成语言模型在多轮文本到SQL任务中的模式和上下文跟踪能力，实现性能显著提升。
Comments Accepted at the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025), Long Paper, 19 pages
Journal ref Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 10690-10708. Association for Computational Linguistics, 2025
