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BEAVER: An Enterprise Benchmark for Text-to-SQL
arXiv.orgExisting text-to-SQL benchmarks have largely been constructed from web tables with human-generated question-SQL pairs. LLMs typically show strong results on these benchmarks, leading to a belief that LLMs are effective at text-to-SQL tasks.
Peter Baile Chen +7 more
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Large Language Model Enhanced Text-to-SQL Generation: A Survey
arXiv.orgText-to-SQL translates natural language queries into Structured Query Language (SQL) commands, enabling users to interact with databases using natural language. Essentially, the text-to-SQL task is a text generation task, and its development is primarily
Xiaohu Zhu +3 more
semanticscholar +1 more source
arXiv.org
Recent In-Context Learning based methods have achieved remarkable success in Text-to-SQL task. However, there is still a large gap between the performance of these models and human performance on datasets with complex database schema and difficult ...
Wenxuan Xie, Gaoche Wu, Bowen Zhou
semanticscholar +1 more source
Recent In-Context Learning based methods have achieved remarkable success in Text-to-SQL task. However, there is still a large gap between the performance of these models and human performance on datasets with complex database schema and difficult ...
Wenxuan Xie, Gaoche Wu, Bowen Zhou
semanticscholar +1 more source
PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-Consistency
International Conference on Database Systems for Advanced ApplicationsRecent advancements in Text-to-SQL (Text2SQL) emphasize stimulating the large language models (LLM) on in-context learning, achieving significant results.
Zhishuai Li +10 more
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Understanding the Effects of Noise in Text-to-SQL: An Examination of the BIRD-Bench Benchmark
Annual Meeting of the Association for Computational LinguisticsText-to-SQL, which involves translating natural language into Structured Query Language (SQL), is crucial for enabling broad access to structured databases without expert knowledge.
Niklas Wretblad +4 more
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MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation
North American Chapter of the Association for Computational LinguisticsText-to-SQL generation enables non-experts to interact with databases via natural language. Recent advances rely on large closed-source models like GPT-4 that present challenges in accessibility, privacy, and latency. To address these issues, we focus on
S. Gorti +7 more
semanticscholar +1 more source