Multi Hop

Multi-hop reasoning, a crucial aspect of artificial intelligence, focuses on solving problems requiring the integration of information from multiple sources or steps. Current research emphasizes improving multi-hop capabilities in various domains, including question answering, knowledge graph traversal, and network routing, often employing techniques like graph neural networks, retrieval-augmented generation, and reinforcement learning algorithms. These advancements are significant for enhancing the capabilities of large language models and improving efficiency in diverse applications such as recommender systems, autonomous systems, and scientific knowledge discovery.