At least since ChatGPT, everyone has heard of transformer-based Large Language Models (LLM). But can the knowledge compressed in LLMs be utilized to improve machine learning models? This may either refer to integrating LMMs to make predictions more accurate. Or, in an eXplainable Artificial Intelligence (XAI) context, to allow for an intuitive understanding of a problem setting by a human expert. One suitable approach may use Knowledge Graphs, which excel at storing structured information. We offer a range of bachelor’s and master theses in this context with application ranging from biomedicine to environmental modeling.