14 citations · 73 across the 14 of their papers we have counts for
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cs.CL2023
Selective Demonstrations for Cross-domain Text-to-SQL
Shuaichen Chang, Eric Fosler-Lussier
Large language models (LLMs) with in-context learning have demonstrated impressive generalization capabilities in the cross-domain text-to-SQL task, without the use of in-domain an…
cs.CL2023★ 12 cited
How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings
Shuaichen Chang, Eric Fosler-Lussier
Large language models (LLMs) with in-context learning have demonstrated remarkable capability in the text-to-SQL task. Previous research has prompted LLMs with various demonstratio…
cs.CL2023★ 10 cited
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
Shuaichen Chang, Jun Wang, Mingwen Dong +13
Neural text-to-SQL models have achieved remarkable performance in translating natural language questions into SQL queries. However, recent studies reveal that text-to-SQL models ar…