Not evaluated
Superpolynomial lower bounds and quasipolynomial reconstruction from deletion traces (family 122)
The gist
On October 6, 2026, OpenAI announced, from an unreleased internal model, three manuscripts on trace reconstruction, with a Lean file.
DiscoverIA status on October 12, 2026: not evaluated, meaning no third-party evaluation found.
AI draft, not reviewedWhat has not been reviewed?
Text written by an AI (DiscoverIA pipeline), on . The status and its sources come from the registry; only the explanatory text has not been reviewed. A reported error is corrected, then the text is reviewed.
Cite this entry
A single status snapshot since Oct 12, 2026: a citation always points to a dated snapshot.
Cite snapshot 1, Oct 12, 2026
APA citation with the dated link
BibTeX @misc, key discoveria-oai-fam-122-superpolynomial-lower-bounds-quasipolynomial-r1
@misc{discoveria-oai-fam-122-superpolynomial-lower-bounds-quasipolynomial-r1,
author = {{DiscoverIA}},
title = {Superpolynomial lower bounds and quasipolynomial reconstruction from deletion traces (family 122)},
howpublished = {DiscoverIA registry, entry oai-fam-122-superpolynomial-lower-bounds-quasipolynomial},
note = {Status “Not evaluated”, snapshot 1, recorded on October 12, 2026. New result},
year = {2026},
url = {https://discoveria.ai/entry/oai-fam-122-superpolynomial-lower-bounds-quasipolynomial#releve-1},
urldate = {2026-10-12}
}Dated link opens this snapshot in the history
To understand ≈ 30 s reading time, estimated
What it changes
If the manuscripts were correct, trace reconstruction could be done in quasipolynomial time, according to one of them. Quasipolynomial time is bounded by 2 to the power of a fixed power of the logarithm of the input size: it stays subexponential. It consists in recovering a string of bits from copies in which bits were deleted at random. A further manuscript concerns quantitative lower bounds for this reconstruction.
What remains unclear
The Lean file (Lean is a language in which a computer checks every step of a proof) is supplied by OpenAI itself, and the repository marks it “unchecked”. The sources read do not say which parts of the manuscripts it covers, and no third-party verification is recorded.
For experts
Sources, method, key facts, status history, report an error
Status
Not evaluated
Recorded on · github.com · 122.md
Step 1 of 4 on the scale: not evaluated. Next step: under review.
- Announced
- Recordednot evaluated
- nextTo follow
What this status means
Source reading : Source read word for word (level 3 of 3)
The result is declared neither right nor wrong.
To move to “Under review”: a public review under way. To “Peer reviewed”: a journal publication or a review by named experts.
Sources
- Main sourcegithub.com · CONTENTS.mdlink only, reading not recorded
- Repositorygithub.com · Uniform-quasipolynomial…link only, reading not recorded
- Repositorygithub.com · A-latest-anchor-induction…link only, reading not recorded
- Repositorygithub.com · quantitative-lower-bounds…link only, reading not recorded
- Lean proofgithub.com · 122.mdpage read word for word
- Lean proofgithub.com · TraceReconstruction.leanlink only, reading not recorded
Method
The three manuscripts of family 122 are as follows. “Quantitative lower bounds for trace reconstruction” is dated September 24, 2026. “Uniform quasipolynomial-time trace reconstruction” is dated October 5, 2026. “A latest-anchor induction with spectrally compact masks for worst-case trace reconstruction” is dated the same day. The file lean/docs/122.md describes the scope of the formalisation, with one Comparator statement (lean/ComparatorChallenges/TraceReconstruction.lean). The family is not among the sources of formalization.yaml; history.md reports no revision. DiscoverIA status: not evaluated, meaning that no third-party evaluation has been found in the sources read. Set on October 12, 2026 from github.com (page read, quotation checked word for word: “describes the scope of the Lean formalization”).
Limits
No named third party: the recorded checks come from the claimant or from a platform tool. The claimant supplies a Lean proof; as of this date, DiscoverIA has found no independent verification of this proof or of the result.
Key facts
- Claimed by
- OpenAI (unreleased internal model)
announced on Oct 6, 2026 - Nature
- new result
- Field
- Theoretical computer science
- In openai/math
- family 122, section “Theoretical computer science”, 3 manuscripts dated Sep 24, 2026
- Lean proof
- supplied by the claimant, marked “unchecked” (not reviewed) in its repository
- Revisions
- none reported by the claimant
- Checked by
- claimant (Lean supplied, not checked by a third party)
- Sources
- 6 : 1 read word for word, 5 links only
- This entry
- AI draft, not reviewed
Status history
Only one observation so far.
- 01
First observation:Not evaluatedCurrent status
Family with a Lean proof supplied by the claimant. No third-party check read; the source marks this proof as not reviewed (“unchecked”).
Source: github.comread word for word
An observation is added; none is ever erased.
In the same set
openai/math: 719 manuscripts in 372 families from an unreleased internal model · entry 119 of 372, by family number
- Not evaluated : The Courtade–Kumar and Hellinger conjectures (family 119)
- Not evaluated : Almost-linear-time exact matching in general graphs (family 120)
- Not evaluated : Almost-linear expected-time approximation of edit distance (family 121)
- Not evaluated : Superpolynomial lower bounds and quasipolynomial reconstruction from deletion traces (family 122)
- Not evaluated : Polynomial-time scheduling on three identical machines (family 124)
- Not evaluated : The approximation threshold for metric k-median (family 125)
- Not evaluated : Exponential semidefinite complexity of perfect matching (family 126)
Report an error or suggest a source
Thank you, your message was sent.
Sending failed. Try again, or write to contact@discoveria.ai.
Is your result listed?What each status requires, correcting this entry, replying to it.