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Creativity: Generating Diverse Questions using Variational Autoencoders

arXiv 1704.03493 ↗First posted 11 Apr 2017cs.CVcited by 24

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Abstract (arXiv)

Generating diverse questions for given images is an important task for computational education, entertainment and AI assistants. Different from many conventional prediction techniques is the need for algorithms to generate a diverse set of plausible questions, which we refer to as "creativity". In this paper we propose a creative algorithm for visual question generation which combines the advantages of variational autoencoders with long short-term memory networks. We demonstrate that our framework is able to generate a large set of varying questions given a single input image.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Apr 2017.

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Citing papers per year: 2021: 7; 2022: 4; 2023: 4; 2024: 4; 2025: 5.

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  1. 2023ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptionscited by 86
  2. 2022CLUTR: Curriculum Learning via Unsupervised Task Representation Learningcited by 19
  3. 2021multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoningcited by 15
  4. 2021Guiding Visual Question Generationcited by 14
  5. 2021Group-based Distinctive Image Captioning with Memory Attentioncited by 13
  6. 2021Diverse and Specific Clarification Question Generation with Keywordscited by 10
  7. 2022K-VQG: Knowledge-aware Visual Question Generation for Common-sense Acquisitioncited by 9
  8. 2021Cross-Modal Generative Augmentation for Visual Question Answeringcited by 7
  9. 2022The Dialog Must Go On: Improving Visual Dialog via Generative Self-Trainingcited by 7
  10. 2022Look, Read and Ask: Learning to Ask Questions by Reading Text in Imagescited by 5
  11. 2023Set Prediction Guided by Semantic Concepts for Diverse Video Captioningcited by 4
  12. 2024ConVQG: Contrastive Visual Question Generation with Multimodal Guidancecited by 4
12 more
  1. 2024ECIS-VQG: Generation of Entity-centric Information-seeking Questions from Videoscited by 2
  2. 2021Goal-driven text descriptions for imagescited by 1
  3. 2023Visual Question Generation in Bengalicited by 1
  4. 2024CAUS: A Dataset for Question Generation based on Human Cognition Leveraging Large Language Modelscited by 1
  5. 2024Ask Questions with Double Hints: Visual Question Generation with Answer-awareness and Region-referencecited by 1
  6. 2025Variational Prefix Tuning for Diverse and Accurate Code Summarization Using Pre-trained Language Modelscited by 1
  7. 2021MMIU: Dataset for Visual Intent Understanding in Multimodal Assistantscited by 0
  8. 2023From text to multimodal: a survey of adversarial example generation in question answering systemscited by 0
  9. 2025Group-based Distinctive Image Captioning with Memory Difference Encoding and Attentioncited by 0
  10. 2025"There Is No Such Thing as a Dumb Question," But There Are Good Onescited by 0
  11. 2025When Big Models Train Small Ones: Label-Free Model Parity Alignment for Efficient Visual Question Answering using Small VLMscited by 0
  12. 2025VideoChain: A Transformer-Based Framework for Multi-hop Video Question Generationcited by 0