mlsanityData to 14 Oct 2026

QuesGenie: Intelligent Multimodal Question Generation

arXiv 2509.03535 ↗First posted 27 Aug 2025cs.CL cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 15 references that are in the map. First posted on arXiv 27 Aug 2025.

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11 of 15 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
  2. 2017Proximal Policy Optimization Algorithmscited by 15,215
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
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  6. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,148
  7. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  8. 2019BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questionscited by 2,183
  9. 2017RACE: Large-scale ReAding Comprehension Dataset From Examinationscited by 861
  10. 2024PaliGemma: A versatile 3B VLM for transfercited by 696
  11. 2024ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wildcited by 79

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  1. 2024The Future of Learning in the Age of Generative AI: Automated Question Generation and Assessment with Large Language Models
  2. 2024Contrastive Learning for Knowledge-Based Question Generation in Large Language Models
  3. 2025A Curriculum Learning Approach to Reinforcement Learning: Leveraging RAG for Multimodal Question Answering
  4. 2024Synthetic Multimodal Question Generation
  5. 2025Leveraging In-Context Learning and Retrieval-Augmented Generation for Automatic Question Generation in Educational Domains
  6. 2026Evolution of Multimodal Question Answering: From Modality-Adaptive Extraction to Unified Language Representation
  7. 2024MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison Feedback
  8. 2026Cognitively Diverse Multiple-Choice Question Generation: A Hybrid Multi-Agent Framework with Large Language Models