select-tiny-sql-tuning-set-schema-coverage-size TEC-0202 · proposedSelect a tiny SQL tuning set for schema coverage, not size
Filter candidate text-to-SQL examples by dual-model difficulty, attach the shortest correct chain-of-thought, score each on four LLM-judged quality dimensions, then use a genetic search to pick a small subset maximizing table/column coverag
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Filter candidate text-to-SQL examples by dual-model difficulty, attach the shortest correct chain-of-thought, score each on four LLM-judged quality dimensions, then use a genetic search to pick a small subset maximizing table/column coverag Filed by the drafting stage from LIMIT: Less Is More for Instruction Tuning in Text-to-SQL (2609.24186) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: BIRD-Dev EX 69.1% and Spider-Dev 88.9% with self-consistency@8 from 796 and 863 samples, versus 67.0% for DB-Explore with 16,457 samples and 63.9-64.2% for OmniSQL trained on 2.5M; ablation removing the coverage term drops SFT accuracy from 65.4% to 58.4%.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
No efficacy claim filed yet. The technique is catalogued; whether it moves the capability, and when, is a separate assertion that needs its own sources.
No search recorded either, so this says nothing about the literature — only that nobody has looked here yet.
Code
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Sources
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