arXiv:2507.03314cs.LOcs.AI2025-07
用部分标签学习提升自动定理证明的推理能力
Partial Label Learning for Automated Theorem Proving
- 将自动定理证明转化为部分标签学习问题
- 在plCoP上验证方法性能显著提升
- 适合研究可解释推理与多路径证明的学者
我们将学习驱动的自动定理证明建模为部分标签学习，首次建立该领域与部分标签学习之间的桥梁，并提供处理学习过程中多种证明路径的理论框架。通过plCoP定理证明器的实验表明，来自部分标签学习领域的算法能够有效提升学习辅助型定理证明器的性能。
原文摘要 · Abstract (English)
We formulate learning guided Automated Theorem Proving as Partial Label Learning, building the first bridge across these fields of research and providing a theoretical framework for dealing with alternative proofs during learning. We use the plCoP theorem prover to demonstrate that methods from the Partial Label Learning literature tend to increase the performance of learning assisted theorem provers.
定理证明部分标签AI推理
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。