arXiv Computation and Language August 31, 2026 By Jiayan Lin, Yujia Liu, Zijin Hong, Zheng Yuan, Yilin Xiao, Hao Chen, Qinggang Zhang, Xiao Huang, Feiran Huang

Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQL

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The paper evaluates 17 paradigm-level configurations of in‑context learning (ICL) text‑to‑SQL pipelines across five common modules, measuring each module’s marginal accuracy contribution and cost for four different backbone models. It finds that execution‑feedback refinement consistently improves accuracy at low cost, while other modules only help under specific backbone conditions. The study also shows that investing in a more elaborate pipeline for a mid‑tier backbone can be more cost‑effective than upgrading to a high‑capability model with a lean pipeline, providing a tiered, cost‑aware guideline that generalizes to additional backbones.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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