elvis@omarsar0 · XAI 摘要
Google 新研究 LEAP 将通用大语言模型封装在智能体框架中，每个步骤基于 Lean 编译器，并依赖验证器反馈进行迭代。同一通用模型解决了全部 12 道 Putnam 2025 问题，并将 Lean-IMO-Bench 一次性解决率从不到 10% 提升至 70%，击败了得分 48% 的专业金牌系统。论文链接：https://arxiv.org/abs/2606.03303。
New research from Google.
Just shows the impressive results you can get from custom agent harnesses.
LEAP wraps a general-purpose LLM in an agentic scaffold that grounds every step in the Lean compiler and iterates against verifier feedback.
The same general model solves all 12 Putnam 2025 problems and lifts Lean-IMO-Bench one-shot solve rate from under 10% to 70%， beating a specialized gold-medal system that scores 48%.
Paper： https://arxiv.org/abs/2606.03303
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