May 14, 2024, 4:49 a.m. | Jun Zhao, Jingqi Tong, Yurong Mou, Ming Zhang, Qi Zhang, Xuanjing Huang

cs.CL updates on

arXiv:2405.06680v1 Announce Type: new
Abstract: Human cognition exhibits systematic compositionality, the algebraic ability to generate infinite novel combinations from finite learned components, which is the key to understanding and reasoning about complex logic. In this work, we investigate the compositionality of large language models (LLMs) in mathematical reasoning. Specifically, we construct a new dataset \textsc{MathTrap}\footnotemark[3] by introducing carefully designed logical traps into the problem descriptions of MATH and GSM8k. Since problems with logical flaws are quite rare in the real …

abstract arxiv cognition components generate human key language language models large language large language models llms logic mathematical reasoning novel reasoning the key type understanding work

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