Step by Step Reasoning

Step-by-step reasoning in artificial intelligence focuses on enabling models to solve complex problems by breaking them down into a sequence of logical steps, mirroring human cognitive processes. Current research heavily utilizes large language models (LLMs) and graph neural networks (GNNs), often incorporating techniques like chain-of-thought prompting, reinforcement learning, and various verification methods to improve accuracy and efficiency. This area is crucial for advancing AI capabilities in diverse fields, from robotics and scientific discovery to question answering and automated reasoning systems, by enhancing model interpretability and robustness.