Engineers at the University of California San Diego have developed a new way to train artificial intelligence systems to ...

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

These student-constructed problems foster collaboration, communication, and a sense of ownership over learning.

Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.

large-scale language models (LLMs), such as OpenAI's GPT-4, has advanced and wide-ranging capabilities, such as generating natural sentences and solving various problems. However, even in elementary ...

Solving word problems is a key component of math curriculum in primary schools. One must have acquired basic language skills to make sense of word problems. So why do children still find certain word ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

If Ms. Smith’s 8th grade algebra class works through 10 word problems in an hour, and Ms. Jones’ class works through 10 equation problems during the same time, which class is likely to learn more math ...