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New NL-to-SQL benchmark and agentic architecture tackle complex enterprise data

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new benchmark and an agentic architecture for natural-language-to-SQL systems designed to handle complex, nested enterprise schemas. The DevRev NL2SQL benchmark includes 900 execution-verified queries and a Semantic Depth Score (SDS) to evaluate analytical reasoning. The proposed cost-aware architecture achieved 91.7% answer correctness on this new benchmark, significantly outperforming existing baselines, and demonstrated competitive performance on the Spider 2.0 Snowflake dataset. AI

IMPACT This research could improve how businesses query complex, nested data using natural language, potentially streamlining data analysis and access.

RANK_REASON The cluster contains a research paper detailing a new benchmark and an associated system for natural-language-to-SQL tasks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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

New NL-to-SQL benchmark and agentic architecture tackle complex enterprise data

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41 / 100
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The cluster contains a research paper detailing a new benchmark and an associated system for natural-language-to-SQL tasks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yoga Sri Varshan Varadharajan, Ajay Yadav, Ritesh Goru, Prateek Chaudhury, Constantine Caramanis, Prateek Jain, Divyateja Pasupuleti, Sunil Kumar Pandey ·

    A Cost-Aware Agentic Architecture for NL-to-SQL over Nested Enterprise Schemas, with a New Benchmark

    arXiv:2609.04641v1 Announce Type: new Abstract: Natural-language-to-SQL systems have ad- vanced rapidly on academic benchmarks, yet production enterprise schemas exhibit graph- like, semi-structured, deeply nested structure that current benchmarks do not measure. We make two comp…

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