{"ID":2877585,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.03535","arxiv_id":"2509.03535","title":"QuesGenie: Intelligent Multimodal Question Generation","abstract":"In today's information-rich era, learners have access to abundant educational resources, but the lack of practice materials tailored to these resources presents a significant challenge. This project addresses that gap by developing a multi-modal question generation system that can automatically generate diverse question types from various content formats. The system features four major components: multi-modal input handling, question generation, reinforcement learning from human feedback (RLHF), and an end-to-end interactive interface. This project lays the foundation for automated, scalable, and intelligent question generation, carefully balancing resource efficiency, robust functionality and a smooth user experience.","short_abstract":"In today's information-rich era, learners have access to abundant educational resources, but the lack of practice materials tailored to these resources presents a significant challenge. This project addresses that gap by developing a multi-modal question generation system that can automatically generate diverse questio...","url_abs":"https://arxiv.org/abs/2509.03535","url_pdf":"https://arxiv.org/pdf/2509.03535v1","authors":"[\"Ahmed Mubarak\",\"Amna Ahmed\",\"Amira Nasser\",\"Aya Mohamed\",\"Fares El-Sadek\",\"Mohammed Ahmed\",\"Ahmed Salah\",\"Youssef Sobhy\"]","published":"2025-08-27T10:45:39Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.AI\"]","methods":"[\"Reinforcement Learning\",\"RLHF\"]","has_code":false}