# GAUSS: Benchmarking Structured Mathematical Skills for Large Language Models

arXiv: https://arxiv.org/abs/2509.18122 · HTML: https://mlsanity.com/paper/2509.18122/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Sep 2025.

## Built on by (most cited first, 2 of 2)

- [Beyond Benchmarks: MathArena as an Evaluation Platform for Mathematics with LLMs](https://mlsanity.com/paper/2605.00674/) (2026)
- [Youtu-LLM: Unlocking the Native Agentic Potential for Lightweight Large Language Models](https://mlsanity.com/paper/2512.24618/) (2025)

## Abstract (arXiv)

We introduce GAUSS (General Assessment of Underlying Structured Skills in Mathematics), a benchmark that evaluates LLMs' mathematical abilities across twelve core skill dimensions, grouped into three domains: knowledge and understanding, problem solving and communication, and meta-skills and creativity. By categorizing problems according to cognitive skills and designing tasks that isolate specific abilities, GAUSS constructs comprehensive, fine-grained, and interpretable profiles of models' mathematical abilities. These profiles faithfully represent their underlying mathematical intelligence. To exemplify how to use the textscGAUSS benchmark, we have derived the skill profile of textscGPT-5-thinking, revealing its strengths and weaknesses as well as its differences relative to textsco4-mini-high, thereby underscoring the value of multidimensional, skill-based evaluation.