Question-Answering on Textbooks by Searching and Ranking

Question Answering is a popular application of NLP. Transformer models trained on big datasets have dramatically improved the state-of-the-art results on Question Answering. The question answering task can be formulated in many ways. The most common application is an extractive question answering on a small context. The SQuAD dataset is a popular dataset where given a passage and a question, the model selects the word(s) representing the answer.