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

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

RIT alumnus Adam Giammarese received the Edward N. Lorenz Early Career Award for his Ph.D. research in chaos theory and ...

Math anxiety is a significant challenge for students worldwide. While personalized support is widely recognized as the most ...

OpenAI’s GPT-5.2 Pro does better at solving sophisticated math problems than older versions of the company’s top large ...

Students from SRM Institute of Science and Technology (SRMIST) made their mark on the international academic arena by taking part in the 2026 Mathematical Contest in Modeling (MCM)—a prestigious ...

"AI can't do math" is no longer true. Our team has been using Creatium Studio's math capabilities to create interactive ...

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

A Russian mathematician has developed a new method for analyzing a class of equations that underpin models in physics and ...

Dr. Leonardos Gkouvelis, researcher at LMU's University Observatory Munich and member of the ORIGINS Excellence Cluster, has ...

Despite the vast differences in human and bee brains, both of us can do mathematics. As we argue in a new paper published in ...