Split text-to-SQL evaluation by database, not by question
Evaluate SQL synthesis on databases and query patterns that never appear in training, so memorized question-query templates cannot be reused.
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.
Evaluate SQL synthesis on databases and query patterns that never appear in training, so memorized question-query templates cannot be reused. Filed by the drafting stage from Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task (1809.08887) 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: Exact-match and per-component F1 for five models under an example split versus a database split of the same corpus; every model scored far lower under the database split, with TypeSQL dropping most (33.0 to 8.2 on test).. 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
Whether a technique works is a claim. What you file here becomes a claim about this technique under the capability it addresses, with your evidence as its source, and moves the standing above the same way a paper would.