← 研踪 PaperTrailarXiv:2611.09048 · v1
LeanDojo-v2: A Comprehensive Library for AI-Assisted Theorem Proving in Lean
首次提交 2026-11-06 14:21
版本更新 2026-11-06 14:21
雷达观测 2026-11-09 11:19
摘要
Building on recent progress in machine learning for formal theorem proving in Lean, we introduce LeanDojo-v2: an end-to-end framework that unifies repository data extraction, LLM fine-tuning, proof search, AI autocompletion, and LLM-assisted theorem proving in a single software library. In addition, we provide Lean4Code, a lightweight IDE that integrates the various features of LeanDojo-v2 through a simple, mathematician-friendly UI. These tools will enable mathematicians and researchers to easily fine-tune language models on domain-specific Lean codebases and experiment with LLM-assisted theorem proving without a complex setup.
作者备注:11 pages, 7 figures, accepted to NeurIPS Math-AI workshop
观测到的版本
相邻记录可能跳过中间版本;首次发现 v2 及以上也会标为版本更新。
v1 · 2026-11-06 14:21 · 最新观测版本
LeanDojo-v2: A Comprehensive Library for AI-Assisted Theorem Proving in Lean
Building on recent progress in machine learning for formal theorem proving in Lean, we introduce LeanDojo-v2: an end-to-end framework that unifies repository data extraction, LLM fine-tuning, proof search, AI autocompletion, and LLM-assisted theorem proving in a single software library. In addition, we provide Lean4Code, a lightweight IDE that integrates the various features of LeanDojo-v2 through a simple, mathematician-friendly UI. These tools will enable mathematicians and researchers to easily fine-tune language models on domain-specific Lean codebases and experiment with LLM-assisted theorem proving without a complex setup.
查看此版本解读 →查看此版本原文 ↗