Tutorial Review

Tutorial reviews synthesize existing research to provide comprehensive introductions to specific topics within a field, aiming to improve accessibility and understanding for a broader audience. Current research focuses on diverse areas, including the development of rigorous methodologies for metaheuristic algorithms, the evaluation of large language models for complex tasks like multi-document question answering and skill composition, and the application of advanced techniques like diffusion models for image enhancement and physics-informed neural networks for quantum system analysis. These tutorials play a crucial role in disseminating knowledge, fostering collaboration, and accelerating progress across various scientific disciplines and practical applications.