Researchers have introduced a new benchmark, DevRev NL2SQL, designed to evaluate natural-language-to-SQL systems on complex, nested enterprise schemas. This benchmark includes 900 execution-verified queries and a new metric called Semantic Depth Score (SDS) to measure analytical reasoning depth. Alongside the benchmark, they presented a cost-aware agentic architecture that achieves 91.7% answer correctness on DevRev NL2SQL, significantly outperforming existing baselines, and remains competitive on the Spider 2.0 Snowflake dataset. AI
IMPACT This work advances the state-of-the-art in NL-to-SQL systems, potentially improving how enterprises interact with complex databases.
RANK_REASON The cluster describes a new academic paper introducing a novel benchmark and an associated system for natural language to SQL translation.
Read on Hugging Face Daily Papers →
- DevRev NL2SQL
- Semantic Depth Score (SDS)
- Spider 2.0 Snowflake
- Yoga Sri Varshan Varadharajan
- Samsung SDS
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