Do Large Language Models Truly Grasp Mathematics? An Empirical
Exploration From Cognitive Psychology

Do Large Language Models Truly Grasp Mathematics? An Empirical Exploration From Cognitive Psychology

19 October 2024

Shuoyoucheng Ma

Zhenhua Wang

Xiaobing Sun

Papers citing "Do Large Language Models Truly Grasp Mathematics? An Empirical Exploration From Cognitive Psychology"

5 / 5 papers shown

Title
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models Iman Mirzadeh Keivan Alizadeh Hooman Shahrokhi Oncel Tuzel Samy Bengio Mehrdad Farajtabar AIMat LRM 100 173 0 07 Oct 2024
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning Zayne Sprague Fangcong Yin Juan Diego Rodriguez Dongwei Jiang Manya Wadhwa Prasann Singhal Xinyu Zhao Xi Ye Kyle Mahowald Greg Durrett ReLM LRM 178 114 0 18 Sep 2024
STOC-TOT: Stochastic Tree-of-Thought with Constrained Decoding for Complex Reasoning in Multi-Hop Question Answering Zhenyu Bi Daniel Hajialigol Zhongkai Sun Jie Hao Xuan Wang LRM 70 1 0 04 Jul 2024
WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning Zhaojian Yu Xin Zhang Ning Shang Yangyu Huang Can Xu Yishujie Zhao Wenxiang Hu Qiufeng Yin SyDa 76 25 0 20 Dec 2023
GLM: General Language Model Pretraining with Autoregressive Blank Infilling Zhengxiao Du Yujie Qian Xiao Liu Ming Ding J. Qiu Zhilin Yang Jie Tang BDL AI4CE 125 1,545 0 18 Mar 2021