Survey on integrating large language models with knowledge-based methods (2025) (www.sciencedirect.com)

A recent survey highlights the growing interest in integrating large language models (LLMs) with knowledge-based methods, aiming to enhance the capabilities and performance of AI systems by leveraging structured information. The approach seeks to address some of the limitations of LLMs, such as their reliance on statistical patterns and potential misinformation, by incorporating verified, domain-specific knowledge. This integration could lead to more reliable outputs and enable AI to better understand and utilize complex data sources. The significance of this development for the AI/ML community lies in its potential to bridge the gap between deep learning techniques and traditional AI methods. By combining the generative power of LLMs with knowledge graphs and expert systems, researchers may pave the way for more robust and contextually aware AI applications across various fields, including healthcare, finance, and education. The implications could redefine how AI systems are built and trained, leading to innovations that improve decision-making processes and enhance user interactions.