Language + Knowledge: The Mutual Reinforcement of Large Language Models and Knowledge Graphs
Large language models (LLMs) have shown great success in many NLP tasks, including question answering, text generation, and more. However, the accuracy, consistency, and explainability of LLMs still hinder their application in many real-world scenarios. To address these problems, researchers have proposed numerous methods to enhance these abilities in LLMs. One of the most promising methods involves combining LLMs with knowledge graphs (KGs), a high-quality, structured knowledge source known for its reasonable explainability. Conversely, LLMs can also be used to improve the quality of knowledge graphs. In this blog, we will discuss the mutual reinforcement between LLMs and KGs. ...