VibeMathedMath problems solved by AI

The Polynomial-Time Low-Degree Conjecture

The low-degree conjecture predicts that when the low-degree advantage between a planted distribution and a uniform null distribution stays bounded, no polynomial-time algorithm can distinguish them. It is false. There is a planted distribution that agrees with the null through the relevant degree, is invariant under vertex relabeling, and is nevertheless distinguished in polynomial time by a rank argument.

Result
Disproved(see note)
Status
Resolved
AI contribution
AI co-developed
Method
Construction
Field
Average-case complexity
Posed by
Samuel B. Hopkins
Year posed
2018
Years open
8y
Solved
2026-07-22
Model
ChatGPT 5.4, 5.5, 5.6
Vendor
OpenAI
Collaborators
Songtao Mao
Verification
Unreviewed
Publication
Preprint
Significance
30 / 100
Disclosed cost
Wikipedia
No dedicated article

What was actually shown

the construction is probabilistic; an explicit uniformly samplable example remains open

What the AI did

The statement on AI use is specific in both directions. The author first put forward constructions from two-dimensional Reed-Muller-style codes and asked whether they could be made invariant under all vertex relabelings while keeping efficient decoding; the model's responses established that they could not, closing off that route. The rank argument that carries the paper was later developed with ChatGPT 5.6 after the author fed it ideas in the spirit of his Remark 2.5. The author independently checked, simplified and organized every proof.

Verification

Single-author arXiv preprint; not yet peer-reviewed.

Source

arXiv:2607.20318 - The Polynomial-Time Low-Degree Conjecture is False

Discussion