🐙 Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations

Project Page: https://mathoctopus.github.io/

Paper: https://arxiv.org/abs/2310.20246.pdf

Code: https://github.com/microsoft/MathOctopus

Introduction

We introduce 🐙 MathOctopus, a series of open-source large language models (LLMs) specifically tailored for multilingual math problem-solving. The MathOctopus models are trained on 🤗 MGSM8KInstruct Dataset, encompassing ten distinct languages. MathOctopus notably outperforms conventional open-source LLMs and exhibits superiority over ChatGPT in few-shot scenarios.

Datasets

MGSM8KInstruct

MSVAMP

Usage

Our dataset and models are all available at Huggingface.

🤗 MGSM8KInstruct_Parallel Dataset

🤗 MGSM8KInstruct_Cross Dataset

🤗 MSVAMP Dataset

Models

*-Parallel refers to our model trained with the parallel-training strategy.

*-Cross refers to our model trained with cross-training strategy.

*-xRFT means we train the model with multilingual rejection sampling.

Overall Results on MGSM

Overall Results on MSVAMP

MathOctopus in English

Intended Uses

These models are trained for research purposes. They are designed to solve multilingual math problems. They can be used in educational software, tutoring systems, or any application where a solution to a math problem is needed.

Citation

Please cite our paper if you use our data, model or code. Please also kindly cite the original dataset papers.

@misc{chen2023breaking,
      title={Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations}, 
      author={Nuo Chen and Zinan Zheng and Ning Wu and Linjun Shou and Ming Gong and Yangqiu Song and Dongmei Zhang and Jia Li},
      year={2023},
      eprint={2310.20246},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}