Hendrycks MATH: Mathematical Problem Solving Benchmark

The MATH dataset is a collection of mathematical problems for evaluating problem-solving capabilities. It was created by researchers including Dan Hendrycks and Collin Burns and published at NeurIPS in 2021. The dataset is hosted on Hugging Face by EleutherAI and was last updated in January 2025.

Use Cases

• Benchmarking AI model performance on mathematical problem solving based on the described problem collection
• Training models for step-by-step mathematical reasoning based on the dataset's structure
• Analyzing the types of mathematical errors made by language models based on the provided problems

Strengths

• Dataset is associated with a peer-reviewed NeurIPS 2021 publication, suggesting academic rigor.
• The dataset is actively maintained, with a last recorded update on Hugging Face in January 2025.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and dataset size are unknown, which may limit suitability assessment.

Provenance

Source

Originally from https://github.com/hendrycks/math, hosted on Hugging Face by EleutherAI.

Collection Method

Likely collected and curated for research purposes, as indicated by the associated academic paper.

Freshness

Last updated 2025-01-12 19:39:12; freshness should be verified.