OpenAI reports the asymptotic average-sensitivity bound for polynomial thresholds

Every degree-at-most-d real polynomial threshold function on the uniform n-dimensional Boolean cube has average sensitivity at most 8d√n for 1≤d≤n.

Sources for this record

What was already known

The exact-extremizer form of the Gotsman–Linial conjecture had counterexamples, but the manuscript says the asymptotic O(d√n) bound remained open.

AI involvement AI-led

OpenAI credits itself as manuscript author and states that its internal frontier model produced the results in this release. Individual human input is not detailed enough to establish task-only autonomy.

OpenAI is named as author on the manuscript, and its release attributes the results to an internal frontier model. The individual human input is not detailed enough to establish autonomy.

Importance Notable

Proves the asymptotic Gotsman–Linial sensitivity bound uniformly in degree and dimension.

Limitations

The sign convention assigns +1 at zero. The result does not identify exact extremizers or settle the refuted stronger formulation.

Technical verification Formal (Lean 4)

OpenAI reports a Lean proof matching the selected claim.

Formal checking

The pinned OpenAI Lean scope note identifies this selected claim.

Checker
OpenAI-reported Lean 4 / Comparator
Scope
Every degree-at-most-d real polynomial threshold function on the uniform n-dimensional Boolean cube has average sensitivity at most 8d√n for 1≤d≤n.
Basis
Reported by the linked checker
Evidence source

Checking a formal statement does not establish that it matches the original problem.

Human understanding Few

Few is the default when evidence for a higher level is insufficient. No named person is documented as explaining the central argument for this assessed contribution.

Correction and publication history

2026-10-18 · publication

Primary manuscript, attribution, prior-work, and scoped checking review for non-notifying local inclusion.

Read this published revision