Theoretical computer science·OpenAI Math·Result 121·Lean formalisation listed

Almost-linear approximation of edit distance

One of the 372 results in OpenAI's public mathematics catalogue, filed under theoretical computer science: 1 preprint, the latest dated 24 September 2026. This page quotes OpenAI's own summary of the claim, links the paper and abstract, and will embed the animation.

Latest paper

An Almost-Linear Approximation Scheme for Edit Distance

24 September 2026 · PDF

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What OpenAI claims

For every fixed rational ε ∈ (0,1), gives a randomized (1+ε) approximation to unit-cost edit distance in worst-case expected time N1+o(1), with success probability at least 2/3. The strings have total length N and polynomially bounded integer symbols. This is an asymptotic guarantee at fixed accuracy. (Lean)

Paper

  1. An Almost-Linear Approximation Scheme for Edit Distance

    · Preprint, not peer reviewed · PDF

    We give a uniform randomized approximation scheme for unit-cost edit distance. For every fixed rational ε ∈ (0,1), it estimates the distance between arbitrary explicitly stored strings of total length N within a factor 1+ε with probability at least 2/3, in worst-case expected time N1+o(1) on a logarithmic-word RAM. The algorithm supports polynomially bounded integer alphabets and returns zero deterministically on equal strings.

Status

Preprint. The paper has 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.

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