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arXiv AI By Mohammadhossein Malekpour, Nour Shaheen, Foutse Khomh, Amine Mhedhbi

Towards Optimizing SQL Generation via LLM Routing

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The paper "Towards Optimizing SQL Generation via LLM Routing" proposes a routing approach for Text-to-SQL tasks that dynamically selects the most cost‑effective large language model (LLM) for each query. Two routing strategies—score‑based and classification‑based—are introduced, achieving accuracy comparable to the best LLM while reducing latency and monetary cost. The authors design the routers for easy training and efficient inference, and demonstrate a practical accuracy‑cost trade‑off on the BIRD dataset.

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