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.

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

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

The method has two main features: it evaluates how AI models reason through problems instead of just checking whether their ...

Do you stare at a math word problem and feel completely stuck? You're not alone. These problems mix reading comprehension ...

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

Over the weekend, Neel Somani, who is a software engineer, former quant researcher, and a startup founder, was testing the math skills of OpenAI’s new model when he made an unexpected discovery. After ...

Abstract: In this paper, a single-channel two-step voltage-time hybrid domain analog-to-digital converter (ADC) is proposed. To achieve high sampling rate and high accuracy, 3.5-bit voltage domain ...

Abstract: Though quite challenging, training a deep neural network for automatically solving Math Word Problems (MWPs) has increasingly attracted attention due to its significance in investigating how ...