4 papers · 1 filter
KELPS: A Framework for Verified Multi-Language Autoformalization via Semantic-Syntactic Alignment
Jiyao Zhang, Chengli Zhong, Hui Xu +2
Modern large language models (LLMs) show promising progress in formalizing informal mathematics into machine-verifiable theorems. However, these methods still face bottlenecks due…
Brain-Inspired Two-Stage Approach: Enhancing Mathematical Reasoning by Imitating Human Thought Processes
Yezeng Chen, Zui Chen, Yi Zhou
Although large language models demonstrate emergent abilities in solving math word problems, there is a challenging task in complex multi-step mathematical reasoning tasks. To impr…
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
Zui Chen, Yezeng Chen, Jiaqi Han +3
Large language models (LLMs) are displaying emergent abilities for math reasoning tasks,and there is a growing attention on enhancing the ability of open-source LLMs through superv…
Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset
Haoyi Wu, Wenyang Hui, Yezeng Chen +3
Mathematical understanding and reasoning are crucial tasks for assessing the capabilities of artificial intelligence (AI). However, existing benchmarks either require just a few st…