DSA Thrust Seminar | Harnessing LLMs for Practical NL2SQL: Paradigms and Challenges
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With the advent of large language models (LLMs), numerous NL2SQL approaches have been proposed, demonstrating exceptional performance across various benchmarks. However, effectively harnessing LLMs for practical NL2SQL applications remains a challenging question due to the different requirements among applications, such as training data, computational resources, etc. In this talk, I will explore the potential paradigms for developing NL2SQL models tailored for real-world scenarios and examine representative approaches within each paradigm. Additionally, I will discuss the research challenges and future directions in this field.
Ju FAN is a professor at Renmin University of China. He received his Ph.D. from Tsinghua University, and worked as a research fellow at National University of Singapore. His research interests are in general area of data management, and his current research focuses on building next-generation data preparation systems. He has published more than 60 papers at top conferences/journals, including SIGMOD, VLDB, ICDE and VLDB Journal. He is a publication chair for VLDB 2023/2024 and regularly serves as PC member for SIGMOD, VLDB and ICDE. He is also a recipient of ACM SIGMOD Research Highlight Award and ACM China Rising Star award.