4 papers
CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive Perspective
Jiayu Liu, Zhenya Huang, Wei Dai +7
Although large language models (LLMs) show promise in solving complex mathematical tasks, existing evaluation paradigms rely solely on a coarse measure of overall answer accuracy,…
From Objectives to Questions: A Planning-based Framework for Educational Mathematical Question Generation
Cheng Cheng, Zhenya Huang, Guanhao Zhao +5
Automatically generating high-quality mathematical problems that align with educational objectives is a crucial task in NLP-based educational technology. Traditional generation met…
End-to-End Graph Flattening Method for Large Language Models
Bin Hong, Jinze Wu, Jiayu Liu +5
In recent years, the breakthrough of Large Language Models (LLMs) offers new ideas for achieving universal methods on graph data. The common practice of converting graphs into natu…
Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning Process
Tong Xiao, Jiayu Liu, Zhenya Huang +4
Geometry Problem Solving (GPS), which is a classic and challenging math problem, has attracted much attention in recent years. It requires a solver to comprehensively understand bo…