High Quality Question

High-quality question generation (HQG) focuses on automatically creating questions that are both linguistically sound and pedagogically effective, addressing limitations in existing question-answering systems and educational tools. Current research emphasizes using large language models (LLMs) with advanced prompting techniques and reinforcement learning to generate questions across various cognitive levels (e.g., Bloom's taxonomy) and for diverse applications like event extraction and multi-document summarization. The development of robust, reference-free evaluation metrics and the exploration of model uncertainty are key challenges, with implications for improving educational resources, information extraction, and human-computer interaction.