Summary of Superclue-math6: Graded Multi-step Math Reasoning Benchmark For Llms in Chinese, by Liang Xu et al.
SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese
by Liang Xu, Hang Xue, Lei Zhu, Kangkang Zhao
First submitted to arxiv on: 22 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A new benchmark dataset called SuperCLUE-Math6 is introduced to evaluate the mathematical reasoning abilities of Chinese language models. This dataset, designed as an upgraded version of GSM8K, consists of over 2000 word problems that require multi-step reasoning and provide natural language solutions. The paper proposes a scheme to quantify the reasoning capability of large models based on their performance on problems with different reasoning steps. Experiments on 13 Chinese models demonstrate a clear stratification of reasoning levels, with top models like GPT-4 showing superior performance. This benchmark fills the gap in Chinese mathematical reasoning benchmarks and provides a comprehensive testbed to advance the intelligence of Chinese language models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary SuperCLUE-Math6 is a new tool to help computer models learn math skills. It’s like a big test with many word problems that need solving. The test helps figure out how good these models are at doing math. Some models, like GPT-4, do better than others. This helps make computers smarter at understanding Chinese language and math. |
Keywords
» Artificial intelligence » Gpt
