Characterizing Paraphrase-Induced Failures in Lean 4 Autoformalization
Lean 4 autoformalization has become increasingly popular in recent years, with frontier language models and open-weight autoformalizers now producing valid formalizations of mathematical theorems. However, these evaluations often rely on single canonical phrasings of theorems and rarely probe whether outputs are robust to natural variation in inputs, while prior work has shown that semantically equivalent paraphrases often induce divergent formal outputs. We study the structure of these divergences in Lean 4 by applying deterministic paraphrase rules to datasets of undergraduate and Olympiad-level math problems. Across four frontier models and three open-weight autoformalizers, we find th...
| Authors | William Feng, Ethan Lou, Aryan Sharma |
|---|---|
| Primary category | cs.LG |
| Published | 25 April 2026 |
| Last updated at source | 17 May 2026 |
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