Question Generator

Question generation (QG) research focuses on automatically creating questions from various sources, including text, images, and knowledge graphs, aiming to improve question answering systems, enhance user interaction with AI, and facilitate data augmentation for various NLP tasks. Current research explores diverse approaches, such as leveraging pre-trained language models, incorporating text structure and context, and employing reinforcement learning techniques to generate high-quality, relevant, and less ambiguous questions. This field is significant because improved QG techniques can lead to more effective educational tools, better conversational AI, and more efficient methods for creating training data for other NLP applications.