ChatGPT, GPT-4 are Large Language Models (LLM). There are four major aspects of LLMs pre-training, adaptation tuning, utilization, ... commonsense reasoning, and symbolic reasoning. Instead of simply ...

A new technique enables large language models like GPT-4 to more accurately solve numeric or symbolic reasoning tasks by writing a Python program in code that generates the correct answer to a ...

However, one interesting fact is that GPT-3 and other large language models perform very well on benchmarks designed for common-sense reasoning, logical reasoning, and ethical reasoning, skills ...

To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...

In "GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models"—currently available as a pre-print paper—the six Apple researchers start with GSM8K's ...

Apple researchers highlight limitations in large language models’ ability to perform accurate mathematical reasoning, citing token sensitivity and probabilistic output.

Despite their impressive language capabilities, large language models have no common sense reasoning, as humans do. For humans, common sense is inherent—it’s part of our natural instinctive ...

Let’s review what leaders should know about AI’s evolution in 2025 and beyond. The Rise Of Agentic AI. Although agentic AI starts with LLMs, it differs substantially from current AI offerings.