BIRD Benchmark — 2 Technical Articles

Aug 20, 2025 · Artificial Intelligence

Boosting Text-to-SQL Accuracy with J‑Schema, Iterative DPO, and Self‑Consistency

This article examines the evolution of Text-to-SQL, introduces the J‑Schema representation and chain-of-thought prompting, applies iterative DPO training and self-consistency voting, and demonstrates how these techniques raise execution accuracy on the BIRD benchmark from 56.6% to 69.2%.

BIRD BenchmarkIterative DPOJ-Schema

0 likes · 11 min read

Boosting Text-to-SQL Accuracy with J‑Schema, Iterative DPO, and Self‑Consistency

JD Tech Talk

Aug 14, 2025 · Artificial Intelligence

Boosting Text-to-SQL Accuracy: J‑Schema, Iterative DPO, and Self‑Consistency

This paper presents a comprehensive approach to improve Text‑to‑SQL performance by introducing J‑Schema for structured database representation, leveraging chain‑of‑thought prompting, applying iterative DPO training, and employing self‑consistency voting, achieving execution accuracy gains from 56.6% to 69.2% on the BIRD benchmark.

BIRD BenchmarkIterative DPOSelf-Consistency

0 likes · 12 min read

Boosting Text-to-SQL Accuracy: J‑Schema, Iterative DPO, and Self‑Consistency