Reasoning Process

Reasoning processes in artificial intelligence, particularly within large language models (LLMs), are a central focus of current research, aiming to understand and improve how these models solve complex problems. This involves investigating various prompting techniques like chain-of-thought (CoT) and tree-of-thoughts (ToT), exploring different model architectures to enhance reasoning capabilities, and developing methods to evaluate not just the accuracy of answers but also the validity and reliability of the underlying reasoning steps. Understanding and improving LLMs' reasoning abilities is crucial for building more trustworthy and robust AI systems with applications across diverse fields, from legal and medical domains to scientific discovery.