Axiom says its AI found solutions to several long-standing math problems, a sign of the technology’s steadily advancing reasoning capabilities.

Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks.

These low-floor, high-ceiling problems support differentiation, challenging all students by encouraging flexible thinking and allowing for multiple solution paths.

Mathematicians excel at handling complexity and uncertainty. Mathematical reasoning strategies aren't just useful for dilemmas involving numbers. We can apply math mindsets to improve our approach to ...

This is a huge advance for AI to make big progress with better reasoning and better math. Artificial general intelligence (AGI) with advanced mathematical reasoning has the potential to unlock new ...

This study introduces MathEval, a comprehensive benchmarking framework designed to systematically evaluate the mathematical reasoning capabilities of large language models (LLMs). Addressing key ...

As a mathematics education researcher, I study how math instruction impacts students' learning, from following standard math procedures to understanding mathematical concepts. Focusing on the latter, ...