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Text-to-SQL Accuracy Collapses on Real-World Data

While text-to-SQL demonstrations appear to be solved, their accuracy plummets when applied to real-world enterprise databases. This significant drop is not due to the language model's intelligence but rather challenges in structure, safety, and correctness. The series will explore seven specific obstacles that current systems face, arguing that a successful approach requires providing the model with a schema map, clearly delineating deterministic from generated outputs, and maintaining data locality. AI

IMPACT Highlights critical limitations of current Text-to-SQL systems on complex enterprise data, suggesting a need for architectural shifts beyond simple model improvements.

RANK_REASON The article discusses limitations and benchmarks of a specific AI capability (Text-to-SQL) rather than a new model release or product launch. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Towards AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Text-to-SQL Accuracy Collapses on Real-World Data

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0 / 100
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Tool
The article discusses limitations and benchmarks of a specific AI capability (Text-to-SQL) rather than a new model release or product launch. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper, product
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High
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103 days old
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COVERAGE [1]

  1. Towards AI TIER_1 English(EN) · venkatesh babu sekar ·

    Text-to-SQL Looks Solved. It Isn’t

    <h4><em>Why text-to-SQL breaks the moment it meets a real schema, and the shape of an architecture that survives it.</em></h4><p><em>Part 1 of 4 on building a conversational analytics engine. This part is the “why.” The next three are the “how.” ~10 min read.</em></p><p>Every tex…