3 papers
cs.AI2025
CuDIP: Enhancing Theorem Proving in LLMs via Curriculum Learning-based Direct Preference Optimization
Shuming Shi, Ruobing Zuo, Gaolei He +3
Automated theorem proving (ATP) is one of the most challenging mathematical reasoning tasks for Large Language Models (LLMs). Most existing LLM-based ATP methods rely on supervised…
cs.AI2025
A Combinatorial Identities Benchmark for Theorem Proving via Automated Theorem Generation
Beibei Xiong, Hangyu Lv, Haojia Shan +3
Large language models (LLMs) have significantly advanced formal theorem proving, yet the scarcity of high-quality training data constrains their capabilities in complex mathematica…
cs.LG2024
Open-Book Neural Algorithmic Reasoning
Hefei Li, Chao Peng, Chenyang Xu +1
Neural algorithmic reasoning is an emerging area of machine learning that focuses on building neural networks capable of solving complex algorithmic tasks. Recent advancements pred…