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cs.CL2024
MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code
Zimu Lu, Aojun Zhou, Ke Wang +5
Code has been shown to be effective in enhancing the mathematical reasoning abilities of large language models due to its precision and accuracy. Previous works involving continued…
cs.CL2024
Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning
Zimu Lu, Aojun Zhou, Ke Wang +5
Direct Preference Optimization (DPO) has proven effective at improving the performance of large language models (LLMs) on downstream tasks such as reasoning and alignment. In this…
cs.CL2024★ 2 cited
MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs
Zimu Lu, Aojun Zhou, Houxing Ren +5
Large language models (LLMs) have exhibited great potential in mathematical reasoning. However, there remains a performance gap in this area between existing open-source models and…