A central focus of my research is on how we can teach computers question answering in the form of passing standardized science exams, as written, using a combination of scientific knowledge and common-sense reasoning skills. In particular, I focus on methods of automated inference that generate explanations for why the answer is correct. The Explanation Bank contains many such resources for explanation-centered inference, including WorldTree and EntailmentBank (book), that help power some of the highest-performing language models available, including the Allen Institute for Artificial Intelligence’s GPT3 competitor, MACAW.