Summary of Stepwise Self-consistent Mathematical Reasoning with Large Language Models, by Zilong Zhao et al.
Stepwise Self-Consistent Mathematical Reasoning with Large Language Models
by Zilong Zhao, Yao Rong, Dongyang Guo, Emek Gözlüklü, Emir Gülboy, Enkelejda Kasneci
First submitted to arxiv on: 24 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Machine Learning (cs.LG)
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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 The paper proposes a novel algorithm called Stepwise Self-Consistent Chain-of-Thought (SSC-CoT) to facilitate complex mathematical reasoning in large language models. SSC-CoT addresses the challenges of selecting critical intermediate results and limited exploration by employing a strategy that selects intermediate steps based on the intersection of reasoning chains. The algorithm also enables the model to discover critical intermediate steps by querying a knowledge graph. To evaluate SSC-CoT, the authors present a new dataset called TriMaster100, which contains 100 trigonometry problems with scored intermediate steps. On this dataset, SSC-CoT triples the effectiveness of state-of-the-art methods. Additionally, the paper benchmarks SSC-CoT on the MATH level 5 dataset and achieves an accuracy of 7.2% higher than the second-best method. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about a new way for computers to solve math problems. It’s hard for computers to do this because they need to take many steps and figure out which steps are most important. The authors created a new algorithm called SSC-CoT that helps computers do this better. They also made a special dataset with 100 math problems that other researchers can use to test their own algorithms. The paper shows that SSC-CoT is much better than other methods at solving these types of math problems. |
Keywords
* Artificial intelligence * Knowledge graph
