SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910315753504768 |
|---|---|
| author | Xu, Liang Xue, Hang Zhu, Lei Zhao, Kangkang |
| author_facet | Xu, Liang Xue, Hang Zhu, Lei Zhao, Kangkang |
| contents | We introduce SuperCLUE-Math6(SC-Math6), a new benchmark dataset to evaluate the mathematical reasoning abilities of Chinese language models. SC-Math6 is designed as an upgraded Chinese version of the GSM8K dataset with enhanced difficulty, diversity, and application scope. It consists of over 2000 mathematical word problems requiring multi-step reasoning and providing natural language solutions. We propose an innovative scheme to quantify the reasoning capability of large models based on performance over problems with different reasoning steps. Experiments on 13 representative Chinese models demonstrate a clear stratification of reasoning levels, with top models like GPT-4 showing superior performance. SC-Math6 fills the gap in Chinese mathematical reasoning benchmarks and provides a comprehensive testbed to advance the intelligence of Chinese language models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_11819 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese Xu, Liang Xue, Hang Zhu, Lei Zhao, Kangkang Computation and Language Artificial Intelligence We introduce SuperCLUE-Math6(SC-Math6), a new benchmark dataset to evaluate the mathematical reasoning abilities of Chinese language models. SC-Math6 is designed as an upgraded Chinese version of the GSM8K dataset with enhanced difficulty, diversity, and application scope. It consists of over 2000 mathematical word problems requiring multi-step reasoning and providing natural language solutions. We propose an innovative scheme to quantify the reasoning capability of large models based on performance over problems with different reasoning steps. Experiments on 13 representative Chinese models demonstrate a clear stratification of reasoning levels, with top models like GPT-4 showing superior performance. SC-Math6 fills the gap in Chinese mathematical reasoning benchmarks and provides a comprehensive testbed to advance the intelligence of Chinese language models. |
| title | SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2401.11819 |