April 1, 2024, 4:47 a.m. | Tonghui Ren, Yuankai Fan, Zhenying He, Ren Huang, Jiaqi Dai, Can Huang, Yinan Jing, Kai Zhang, Yifan Yang, X. Sean Wang

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.20014v1 Announce Type: cross
Abstract: Large Language Model (LLM) techniques play an increasingly important role in Natural Language to SQL (NL2SQL) translation. LLMs trained by extensive corpora have strong natural language understanding and basic SQL generation abilities without additional tuning specific to NL2SQL tasks. Existing LLMs-based NL2SQL approaches try to improve the translation by enhancing the LLMs with an emphasis on user intention understanding. However, LLMs sometimes fail to generate appropriate SQL due to their lack of knowledge in organizing …

abstract arxiv basic cs.ai cs.cl cs.db language language model language understanding large language large language model llm llms making natural natural language role sql sql generation tasks translation type understanding writer

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