A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges
Year: 2025
Type: conference-paper
Abstract: Mathematical reasoning, a core aspect of human cognition, is vital across many domains, from educational problem-solving to scientific advancements.As artificial general intelligence (AGI) progresses, integrating large language models (LLMs) with mathematical reasoning tasks is becoming increasingly significant.This survey provides the first comprehensive analysis of mathematical reasoning in the era of multimodal large language models (MLLMs).We review over 200 studies published since 2021, and examine the state-of-theart developments in Math-LLMs, with a focus on multimodal settings.We categorize the field into three dimensions: benchmarks, methodologies, and challenges.In particular, we explore multimodal mathematical reasoning pipeline, as well as the role of (M)LLMs and the associated methodologies.Finally, we identify seven major challenges hindering the realization of AGI in this domain, offering insights into the future direction for enhancing multimodal reasoning capabilities.This survey serves as a critical resource for the research community in advancing the capabilities of LLMs to tackle complex multimodal reasoning tasks.
Authors: Yibo Yan, Jiamin Su, Jianxiang He, Fangteng Fu, Xu Zheng, Yuanhuiyi Lyu, Kun Wang, Shen Wang, Qingsong Wen, Xuming Hu
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4412888230