Insights into Natural Language Database Query Errors: From Attention Misalignment to User Handling Strategies
Zheng Ning,
Yuan Tian,
Zheng Zhang
et al.
Abstract:Querying structured databases with natural language (NL2SQL) has remained a difficult problem for years. Recently, the advancement of machine learning (ML), natural language processing (NLP), and large language models (LLM) have led to significant improvements in performance, with the best model achieving ∼ 85% percent accuracy on the benchmark Spider dataset. However, there is a lack of a systematic understanding of the types, causes, and effectiveness of error-handling mechanisms of errors for erroneous quer… Show more
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