arXiv:2606. 12387v1 Announce Type: cross Abstract: Large Language Models (LLMs) have democratized database access through Text-to-SQL, but moving from prototypes to production remains difficult.
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ProcArena is a new benchmark for evaluating large language models on natural‑language to PL/SQL translation tasks. It contains 3,998 executable tasks across 157 databases, covering nine development subscenarios in PostgreSQL and Oracle, and supports both direct generation and interactive multi‑turn scenarios. Experiments on seven models show that even the best performers achieve only about 62% accuracy in direct mode and 58% in interactive mode, highlighting the difficulty of realistic NL‑to‑PL/SQL development.
arXiv:2607. 06229v1 Announce Type: cross Abstract: Major cloud data platforms now expose large language model capabilities as native SQL functions, enabling analysts to perform classification, filtering, sentiment analysis, extraction, similarity search, and aggregation within ordinary SQL queries.
arXiv:2609.37233v1 Announce Type: cross Abstract: Datalog underpins reasoning tasks such as program analysis, but its programs are hard to write. Existing synthesizers automate this task but require...
arXiv:2608. 15145v1 Announce Type: new Abstract: Large Language Models (LLMs) have been increasingly adopted in Text-to-SQL systems, yet SQL errors remain a major obstacle in real-world Text-to-SQL inference pipelines.
arXiv:2608. 11889v1 Announce Type: cross Abstract: Prompting-based (\textit{i}.
arXiv:2607. 20489v1 Announce Type: new Abstract: Text-to-SQL has advanced rapidly with large language models, but complex database queries still require reasoning beyond one-shot generation, including multi-step decomposition, execution-based diagnosis, and targeted correction.