A survey on neural question generation : Methods, applications, and prospects

• Main Authors: GUO, Shasha, LIAO, Lizi, LI, Cuiping, CHUA, Tat-Seng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Natural language processing; NLP; Question answering; Language generation; Artificial Intelligence and Robotics; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/9699; https://ink.library.smu.edu.sg/context/sis_research/article/10699/viewcontent/2402.18267v2.pdf
• Institution: Singapore Management University

In this survey, we present a detailed examination of the advancements in Neural Question Generation (NQG), a field leveraging neural network techniques to generate relevant questions from diverse inputs like knowledge bases, texts, and images. The survey begins with an overview of NQG’s background,...