SIRIUS-SQL: Anchoring Multi-Candidate Text-to-SQL in Execution Feedback

• URL: http://arxiv.org/abs/2606.01246v1
• Date: Sun, 31 May 2026 13:59:09 GMT
• Title: SIRIUS-SQL: Anchoring Multi-Candidate Text-to-SQL in Execution Feedback
• Abstract summary: Text-to-on complex schemas is unreliable on a single pass, so recent systems generate multiplesql candidates and let voting filter out errors.<n>Voting alone is not enough, because the multi-candidate recipe has three coupled weaknesses.<n>We present SIRIUS--32B, which addresses all three weaknesses.
• Score: 26.80964126227997
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Text-to-SQL on complex schemas is unreliable on a single pass, so recent systems generate multiple SQL candidates and let voting filter out errors. Yet voting alone is not enough, because the multi-candidate recipe has three coupled weaknesses: 1) sampling more from a single generator produces increasingly redundant candidates, 2) existing pipelines apply one generic correction to every non-clean execution result, while runtime errors, timeouts, and empty results each indicate a different distance from correctness, and 3) existing selectors rely on a single angle such as result-majority voting or pairwise SQL comparison, missing what other angles would have caught. We present SIRIUS-SQL, which addresses all three weaknesses. A difficulty-smoothing RL recipe trains SIRIUS-32B to generate diverse executable SQL candidates, paired with a generalist LLM that fills in gaps left by the specialist. An execution-grounded lifecycle classifies each outcome and applies targeted repair before candidates re-enter the pool. A confidence-gated hybrid selector combines execution-result agreement with pairwise SQL-form judgment, escalating only near-tied cases to a deterministic structural check. SIRIUS-SQL reaches 75.88% on BIRD dev and 91.20% on SPIDER test. Two of three generalist pairings surpass Agentar-Scale-SQL, the strongest published multi-candidate system on BIRD dev.

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