Machine learning is used to make buildings more energy-efficient, but the models are often hard to understand. Researchers have looked at ways to make these models easier to interpret. They found that there are challenges in using different terms to describe model interpretability, comparing performance, and providing full explanations. More work is needed to improve how we understand these complex models for better energy management in buildings.