Papers by Yurong Mou

1 papers
Exploring the Compositional Deficiency of Large Language Models in Mathematical Reasoning Through Trap Problems (2024.emnlp-main)

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Challenge: Current LLMs lack systematic compositionality, and therefore cannot serve as reliable cognitive models.
Approach: They propose to introduce logical traps into the original problems of MATH and GSM8K to investigate the compositionality of large language models in mathematical reasoning.
Outcome: The proposed model can generate infinite combinations from finite learned components.

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