Combinatorics·OpenAI Math·Result 175·Lean formalisation listed
Talagrand’s expectation thresholds, discrete convexity, and graph decompositions
One of the 372 results in OpenAI's public mathematics catalogue, filed under combinatorics: 3 preprints, the latest dated 5 October 2026. This page quotes OpenAI's own summary of the claim, links the papers and abstracts, and embeds the animation.
In one line: OpenAI reports a result titled ‘Talagrand’s expectation thresholds, discrete convexity, and graph decompositions’ (combinatorics) in 3 preprints, the latest dated 5 October 2026. It has not been peer reviewed. The channel's animation, Every OpenAI Math Result, Part 2 of 4: PCP for PPAD, Birkhoff Conjecture and 82 More, is on YouTube.
Chapter 24 of 84 in Every OpenAI Math Result, Part 2 of 4: PCP for PPAD, Birkhoff Conjecture and 82 More · starts at 7:58 · watch from there on YouTube →
What OpenAI claims
Proves that integral and fractional expectation thresholds differ by at most a universal factor, and resolves Talagrand's discrete-convexity conjecture. An application proves the Ascoli–He–Park–Talagrand graph-decomposition conjecture: every graph's edges split into a universally bounded number of fixed pieces, each with containment threshold at most a universal constant times the original graph's integral expectation threshold. The pieces' embeddings need not agree on shared vertices. (Lean)
Papers (3)
Graph Decompositions at the Integral Expectation Threshold
OpenAI's abstract We prove the graph-decomposition conjecture of Ascoli, He, Park, and Talagrand. Every graph admits a partition into a universally bounded number of fixed edge pieces, each having ordinary containment threshold at most a universal constant times the original graph's integral expectation threshold. The partition is chosen before sampling the random host, and the separate embeddings of the pieces need not agree on shared vertices.
Integral and fractional expectation thresholds are equivalent
OpenAI's abstract We prove Talagrand's conjecture that integral and fractional expectation thresholds are within a universal constant factor, with the same covering budget.
Talagrand’s discrete-convexity conjecture
OpenAI's abstract We prove Talagrand's discrete-convexity conjecture. There is a universal integer k such that, whenever an arbitrary family has Bernoulli product measure at least 1-1/k, the sets not contained in a union of k members admit a cover of total cost at most 1/2 at the same density.
Status
Preprint. The papers have not been independently reviewed. Treat the result as OpenAI's claim until other mathematicians have checked it. If a video exists, it illustrates the statement; it is not the proof.
Quick answers
- Is it proven?
- Not independently yet. OpenAI posted 3 preprints, the latest dated 5 October 2026; it has not been peer reviewed, so treat the result as OpenAI's claim until other mathematicians have checked it.
- What exactly does OpenAI claim?
- Proves that integral and fractional expectation thresholds differ by at most a universal factor, and resolves Talagrand's discrete-convexity conjecture. An application proves the Ascoli–He–Park–Talagrand graph-decomposition conjecture: every graph's edges split into a universally bounded number of fixed pieces, each with containment threshold at most a universal constant times the original graph's integral expectation threshold. The pieces' embeddings need not agree on shared vertices. (Lean)
- Where is the proof?
- In the paper, Graph Decompositions at the Integral Expectation Threshold (PDF).
- Is there a video?
- Yes, on YouTube (29:10, chapter 24).
Also in
- Chapter 9 of 10 in Borsuk's Conjecture Fails in Dimension 9, Sidorenko's Conjecture and 8 More · starts at 2:47 · watch from there on YouTube →
The video
Every OpenAI Math Result, Part 2 of 4: PCP for PPAD, Birkhoff Conjecture and 82 More · Compilation · 29:10 · chapter 24 from 7:58 · description, sources and chapters →
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