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納維–斯托克斯方程的形式化翻譯可能偏離原始證明
纳维-斯托克斯方程:翻译中的迷失
AI 導讀
arXiv 論文指出,AI 把數學自然語言論證自動轉成 Lean 並完成機械驗證,仍不足以確認形式化內容忠實呈現原文。論文指出,消解數學自然語言歧義以進行語義忠實翻譯,其複雜度在 SCI 階層中可任意高(SCI = ∞)。
正文
Abstract:Autoformalisation is increasingly used to verify mathematical texts, including those generated by AI, as in OpenAI's announced proof of blow-up of solutions to the Navier-Stokes equations. In this process, an AI system translates the text from a natural language (NL) into a formal language such as Lean. Once this translation is done, the argument expressed in the formal language can easily be mechanically verified. The purpose of this article is to demonstrate why this process may offer no confidence in the original NL argument, owing to the various difficulties in performing the translation semantically faithfully. In particular, we highlight that the problem of resolving ambiguities in mathematical NL text, which is necessary in order to provide semantically faithful translation, is arbitrarily high up in the Solvability Complexity Index (SCI) hierarchy/arithmetical hierarchy (the SCI $= \infty$). Hence, informally, providing semantically faithful AI autoformalisation is harder than any computational problem including the Halting problem (which has SCI $= 1$). To demonstrate the effect of this result we provide several examples of AI mistranslations of NL statements and proofs into Lean in practice, resulting in mismatches between NL proofs and their Lean `verifications'. These include OpenAI's announced Navier-Stokes proof. In particular, we show that the formalised Lean proof does not correspond to the NL proof of blow-up of solutions to the Navier-Stokes equations.
| Comments: | 25 pages, 4 Figures |
| Subjects: | Analysis of PDEs (math.AP); Artificial Intelligence (cs.AI); Logic (math.LO) |
| MSC classes: | 35Q30, 03Dxx (primary) and 68V20, 68Txx, 03B65 (secondary) |
| Cite as: | arXiv:2610.08144 [math.AP] |
| (or arXiv:2610.08144v1 [math.AP] for this version) | |
| https://doi.org/10.48550/arXiv.2610.08144 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Alexander Bastounis [view email]
[v1]
Tue, 6 Oct 2026 10:58:01 UTC (1,080 KB)
來源:Hacker News 熱門(buzzing.cc 中文翻譯) · arxiv.org