Problem detail · source-aware

Erdős Problem #550

candidateconfidence 50%

VibeMathed reports this item as candidate. VibeMath preserves that report as a source assertion and has not independently authored a plain-language mathematical explanation.

Precise statement

Let $m_1\leq\cdots\leq m_k$ and $n$ be sufficiently large. If $T$ is a tree on $n$ vertices and $G$ is the complete multipartite graph with vertex class sizes $m_1,\ldots,m_k$, prove that $R(T,G)\leq (\chi(G)-1)(R(T,K_{m_1,m_2})-1)+m_1$.

The source statement is reproduced for indexing with attribution. Mathematical correctness requires domain-expert or mechanical review. VibeMath has not independently audited statement fidelity, correctness, priority, or novelty.

What AI did

ChatGPT

The paper's disclosure states ChatGPT was used for ideation, formulation, proof exploration and refinement, narrowing the search space, programming and orchestration, with the author taking responsibility for the final contents; forum readers describe it as an affirmative paper almost purely by AI.

Provider: OpenAI · Prompt public: unknown · Independence: unknown

Verification boundary

unreviewed

AI screenings on the forum initially flagged issues that turned out to be PDF-parsing artifacts; a re-run against the TeX source found no issues. No independent human review yet, and the site's owner is explicitly reserving judgement.

Correctness: unknown · statement fidelity: unaudited · peer review: none

Timeline

  1. erdosproblems.com/550

    Claimed proved in a preprint of E. Li; erdosproblems.com still lists the problem open pending human review

Known method families

argument (source-reported)

Source-reported tools: argument.

Independent: unknown · difference confidence: 0

What remains uncertain

VibeMath has not independently audited the mathematical statement, proof, or novelty claim.

  • The source status is candidate and must not be represented as solved.
  • VibeMath has not independently verified the mathematical claim.
  • AI-attempt independence and training-data exposure are unknown unless explicitly documented.
  • VibeMath has not independently audited the mathematical statement, proof, or novelty claim.