AlphaGeometry2在奥数几何题上达到金牌水平,解题率超84%
Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2
- 扩展语言能力以处理运动、角度方程等复杂几何问题
- 解题率从54%提升至84%,覆盖率达88%
- 支持自然语言输入,适合数学竞赛与AI推理研究者
我们提出AlphaGeometry2(AG2),是2024年AlphaGeometry的显著升级版本,现已在奥数几何题上超越平均金牌选手表现。通过扩展原始语言以应对物体运动、角度/比例/距离的线性方程问题,并支持非构造性题目,使对2000-2024年国际数学奥林匹克(IMO)几何题的覆盖率从66%提升至88%。搜索过程借助Gemini架构增强语言建模能力,并引入新型知识共享机制,实现搜索树间高效通信。结合符号引擎优化与合成数据生成,整体解题率在近25年所有几何题上达84%,较此前提升显著。AG2亦参与实现2024年IMO银牌水平系统。最后,我们报告了将AG2用于全自动自然语言输入几何题求解的进展。代码已开源。
原文摘要 · Abstract (English)
We present AlphaGeometry2 (AG2), a significantly improved version of AlphaGeometry introduced in (Trinh et al., 2024), which has now surpassed an average gold medalist in solving Olympiad geometry problems. To achieve this, we first extend the original AlphaGeometry language to tackle problems involving movements of objects, and problems containing linear equations of angles, ratios, and distances. This, together with support for non-constructive problems, has markedly improved the coverage rate of the AlphaGeometry language on International Math Olympiads (IMO) 2000-2024 geometry problems from 66% to 88%. The search process of AG2 has also been greatly improved through the use of Gemini architecture for better language modeling, and a novel knowledge-sharing mechanism that enables effective communication between search trees. Together with further enhancements to the symbolic engine and synthetic data generation, we have significantly boosted the overall solving rate of AG to 84% on all geometry problems over the last 25 years, compared to 54% previously. AG2 was also part of the system that achieved the silver-medal standard at IMO 2024 https://deepmind.google/blog/ai-solves-imo-problems-at-silver-medal-level/. Finally, we report progress towards using AG2 as a part of a fully automated system that reliably solves geometry problems from natural language input. Code: https://github.com/google-deepmind/alphageometry2.
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