FairyTailor: A Multimodal Generative Framework for Storytelling
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Abstract (arXiv)
Storytelling is an open-ended task that entails creative thinking and requires a constant flow of ideas. Natural language generation (NLG) for storytelling is especially challenging because it requires the generated text to follow an overall theme while remaining creative and diverse to engage the reader. In this work, we introduce a system and a web-based demo, FairyTailor, for human-in-the-loop visual story co-creation. Users can create a cohesive children's fairytale by weaving generated texts and retrieved images with their input. FairyTailor adds another modality and modifies the text generation process to produce a coherent and creative sequence of text and images. To our knowledge, this is the first dynamic tool for multimodal story generation that allows interactive co-formation of both texts and images. It allows users to give feedback on co-created stories and share their results.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 27 of its 48 references that are in the map. First posted on arXiv 13 Jul 2021.
Builds on
27 of 48 references.
References · 27
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15 more
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Built on by
Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 3; 2026: 2.
9 papers.
- 2025Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corporacited by 86
- 2024Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corporacited by 48
- 2024DataNarrative: Automated Data-Driven Storytelling with Visualizations and Textscited by 25
- 2023Toward Artificial Empathy for Human-Centered Design: A Frameworkcited by 6
- 2025Guiding Generative Storytelling with Knowledge Graphscited by 2
- 2025Influence-driven Curriculum Learning for Pre-training on Limited Datacited by 2
- 2022VScript: Controllable Script Generation with Visual Presentationcited by 1
- 2026DATAREEL: Automated Data-Driven Video Story Generation with Animationscited by 1
- 2026Does Episodic Memory Help Close the Lexical Frequency Gap in Sensitivity to Syntactic Contrasts? A Test Using Retrieval-Augmented Language Modelscited by 0
- 2026Does Episodic Memory Help Close the Lexical Frequency Gap in Sensitivity to Syntactic Contrasts? A Test Using Retrieval-Augmented Language Models24 Aug 2026
- 2026DATAREEL: Automated Data-Driven Video Story Generation with Animations28 Apr 2026
- 2025Influence-driven Curriculum Learning for Pre-training on Limited Data21 Aug 2025
- 2025Guiding Generative Storytelling with Knowledge Graphs30 May 2025
- 2025Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora10 Apr 2025
- 2024Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora6 Dec 2024
- 2024DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts9 Aug 2024
- 2023Toward Artificial Empathy for Human-Centered Design: A Framework19 Mar 2023
- 2022VScript: Controllable Script Generation with Visual Presentation1 Mar 2022