Magenta: Closing the Loop Between Mathematical Reasoning and Lean Verification
Most of mathematical knowledge has been communicated through so-called informal use of mathematics and natural language. With large language models (LLMs) being highly adept in using natural language, they achieve strong performance, yet not perfect, in informal mathematical reasoning. Restraining LLMs to informal reasoning misses out on the opportunity to use the discrete verification abilities that machines offer through machine-checkable proofs. In this paper, we bridge the gap between informal and formal reasoning by integrating Lean signals into the informal reasoning process. We introduce Magenta, a training-free agentic pipeline that, given only a natural-language problem, produces...
| Authors | Joshua Ong Jun Leang, Haonan Li, Zheng Zhao et al. |
|---|---|
| Primary category | cs.AI |
| Published | 10 September 2026 |
| Last updated at source | 21 September 2026 |
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