Can We Really Trust Knowledge Graph Embeddings? A Simple Guide to Quantifying Uncertainty in Predictions of KGE Models with Statistical Guarantees
Large-language models (LLMs) have the potential to support a wide range of applications. However, they are ill-suited for query answering in high-stake domains like medicine because they generate answers at random and their answers are typically not robust - even the same query can result in different answers when prompted multiple times.
