AI Crushes the Competition in Math, Machine Learning, and Open-Ended Tasks—Here’s How It Did It

Editor's Note: This is Part 4 of 5 of a research study detailing the development of Data Interpreter, a solution for various data science and real-world tasks. Read the rest below.

Table of Links

• Abstract and 1 Introduction

• 2 Related Work

• 3 Methodology and 3.1 Dynamic planning with Hierarchical Structure

  • 3.2 Tool utilization and generation
  • 3.3 Enhancing reasoning with verification and experience

• 4 Experiments

  • 4.1 Experimental Setup
  • 4.2 Main Result
  • 4.3 Ablation Study

• 5 Conclusion and References

  A. Additional Results

  B. Implementation Results

  C. Details of Datasets

4 EXPERIMENTS

4.1 EXPERIMENTAL SETUP

4.1.1 DATASET

MATH dataset

The MATH dataset (Hendrycks et al., 2021) comprises 12,500 problems, with 5,000 designated as the test set, covering various subjects and difficulty levels ...