Question-Answer-Generation

Question-Answer Generation (QAG) is a significant branch of Natural Language Processing (NLP) that aims to automatically generate high-quality question-answer pairs. Its core objective is to extract key information from given text using deep learning and language model technologies, generating question-answer pairs that conform to semantic and grammatical norms. QAG has extensive application value in education, intelligent Q&A systems, knowledge management, and other fields, effectively enhancing the efficiency and accuracy of information retrieval and user interaction.