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Systematic study reveals design choices impact value linking accuracy in text-to-SQL systems, suggesting improvements.
Value linking in text-to-SQL systems is the problem of associating values mentioned or implied within a NL query with their database entries. Despite existing efforts, their performance and comparative effectiveness remain unexplored. This work provides the first systematic study focused exclusively on value linking. First, we present a taxonomy that encapsulates the key steps and design choices for value linking. To enable a thorough analysis, we introduce VLD-Bench, a new, challenging benchmark that incorporates 18 categories of lexical and semantic discrepancies between values referenced in the queries and database entries. Our evaluation shows that state-of-the-art text-to-SQL systems suffer up to a 64% drop in execution accuracy due to value linking errors. A fine-grained analysis reveals how design choices impact robustness to linguistic variation and system latency, offering key insights and directions for future research.
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Koukouvinis et al. (2026) studied this question.
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