Introduction Large language models (LLMs) have demonstrated incredible reasoning abilities, penetrating an increasing number of domains in our lives. These models achieve such capabilities by pretraining on vast amounts of human language. A common and powerful method to extract the most accurate responses from these models is called Chain-of-Thought (CoT), where we encourage the model to generate solutions step-by-step, providing reasoning for reaching the final answer. However, the reasoning of...