Visored: A Controlled-Natural-Language Prover for LLM-Generated Mathematics
We present a dependent-type-based prover designed around the way LLMs (and humans) tend to write mathematics, complementing existing systems such as Lean and Rocq. Its core design choices are a surface that imitates mathematical natural language and a rule-driven automation layer that closes the routine steps a textbook would omit, so that an accepted proof can be re-emitted as a checked Lean file. Early experiments suggest that, even without any prover-specific training data, LLMs can learn to use it effectively on the miniF2F benchmark. Lean output excerpts: https://github.com/xiyuzhai-husky-lang/visored/
| Authors | Xiyu Zhai, Xinyi Chen, Yiping Wang et al. |
|---|---|
| Primary category | cs.PL |
| Published | 16 June 2026 |
| Last updated at source | 16 June 2026 |
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