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LeanFlow system translates math papers into Lean projects using LLM agents

Researchers have developed LeanFlow, a system designed to translate mathematical papers into executable Lean projects. Through case studies on number theory and measure theory papers, they evaluated different workflow mechanisms and LLM agents, specifically Kimi2.6 and GPT5.5. The study found that Kimi2.6 could complete projects within a call budget using a full workflow, while GPT5.5 also completed all variants and showed cost efficiency. LeanFlow demonstrated strong performance on benchmarks, achieving 75.7% BEq+ on the RLM25 PFR slice and successfully solving all five ICML 2026 AI for Math TCS challenge projects. AI

IMPACT This research could advance automated formalization of mathematical proofs, potentially improving AI's ability to assist in rigorous scientific discovery.

RANK_REASON The item is a research paper detailing a new system and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]

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LeanFlow system translates math papers into Lean projects using LLM agents

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Lazar Milikic, Simon Guilloud, Khanh Nguyen, Viktor Kuncak ·

    LeanFlow: A Case Study in Workflow-Driven Lean Autoformalization

    arXiv:2607.20503v1 Announce Type: new Abstract: We present and evaluate LeanFlow, an LLM agent system specialized for translating mathematical papers into buildable Lean projects. Recent verifier-in-the-loop systems show that large formal artifacts can be produced, but it remains…