lean artifact · pending
Artifact ↗Polynomial-time approximate counting and uniform sampling of contingency tables with arbitrary margins
FPRAS manuscript: one randomized algorithm counts nonnegative integer matrices with prescribed row sums, column sums and entry bounds (zeros allowed) within relative error with probability , using unbiased bits and a polynomial bound in the input length, and on every execution. Sampling manuscript: for ordinary tables, an almost-uniform sampler (TV error ) in worst-case polynomial bit time and an exactly uniform sampler in expected polynomial bit time in . Exponents are deliberately large; the results are complexity classifications, not practical algorithms, and the exact sampler is polynomial only in expectation.
Exact FrontierDelta
Scope and record
Occurred: Sep 24, 2026
Delta type: SOURCE CLAIM
Assumptions: VibeMathed verification: lean-checked. Publication: announcement. AI contribution: ai-discovered. VibeMathed editorial classifications, scores, notes, relations, and dataset structure are CC BY 4.0. Source statements and linked content retain their own rights.
Canonical aliases: Polynomial-time approximate counting and uniform sampling of contingency tables with arbitrary margins · Counting and sampling contingency tables
Confidence: Not scored
Registry verification: lean checked · announcement · candidate
Attribution
VibeMathed
registry · event recorded by
Unreleased internal OpenAI model
model · ai model contributor · OpenAI
Artifacts and verifiers
Compute record
No linked compute attempts recorded.
Lineage and corrections
VibeMathed record: Polynomial-time approximate counting and uniform sampling of contingency tables with arbitrary margins evidence for this event
This event attributed to Unreleased internal OpenAI model
Lean: OAI/Combinatorics/ContingencyTables/UnconditionalMain.lean evidence for this event
Exact uniform sampling of contingency tables with arbitrary margins (companion) evidence for this event
Polynomial-time approximate counting and uniform sampling of contingency tables with arbitrary margins evidence for this event
FPRAS manuscript: one randomized algorithm counts nonnegative integer matrices with prescribed row sums, column sums and entry bounds (zeros allowed) within relative error with probability , using unbiased bits and a polynomial bound in the input length, and on every execution. Sampling manuscript: for ordinary tables, an almost-uniform sampler (TV error ) in worst-case polynomial bit time and an exactly uniform sampler in expected polynomial bit time in . Exponents are deliberately large; the results are complexity classifications, not practical algorithms, and the exact sampler is polynomial only in expectation. parent of this event
Cryan, Dyer, Randall, Approximately counting integral flows and cell-bounded contingency tables (SICOMP 2010) evidence for this event
Polynomial-time approximate counting and uniform sampling of contingency tables with arbitrary margins parent of this event
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