Jindong Wang, a researcher, and Steven Euijong Whang, an associate professor at KAIST and co-author of the ERBench paper, dive into the innovative ERBench project designed to evaluate large language models (LLMs). They discuss leveraging relational databases to tackle inaccuracies and enhance response assessments. The duo highlights the importance of integrity constraints in crafting multi-hop questions, as well as the varied performance metrics needed to ensure model trustworthiness, especially in addressing LLM hallucinations.