mlsanityData to 7 Oct 2026

Envisioning Narrative Intelligence: A Creative Visual Storytelling Anthology

arXiv 2310.04529 ↗First posted 6 Oct 2023cs.CLcited by 7

Not on the map. Why?

Abstract (arXiv)

In this paper, we collect an anthology of 100 visual stories from authors who participated in our systematic creative process of improvised story-building based on image sequences. Following close reading and thematic analysis of our anthology, we present five themes that characterize the variations found in this creative visual storytelling process: (1) Narrating What is in Vision vs. Envisioning; (2) Dynamically Characterizing Entities/Objects; (3) Sensing Experiential Information About the Scenery; (4) Modulating the Mood; (5) Encoding Narrative Biases. In understanding the varied ways that people derive stories from images, we offer considerations for collecting story-driven training data to inform automatic story generation. In correspondence with each theme, we envision narrative intelligence criteria for computational visual storytelling as: creative, reliable, expressive, grounded, and responsible. From these criteria, we discuss how to foreground creative expression, account for biases, and operate in the bounds of visual storyworlds.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 24 of its 92 references that are in the map. First posted on arXiv 6 Oct 2023.

Builds on

24 of 92 references.

References · 24

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  3. 2016Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotationscited by 2,646
  4. 2015Microsoft COCO Captions: Data Collection and Evaluation Servercited by 1,447
  5. 2015Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Modelscited by 1,352
  6. 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
  7. 2014Show and Tell: A Neural Image Caption Generatorcited by 877
  8. 2016A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Storiescited by 413
  9. 2015Skip-Thought Vectorscited by 321
  10. 2018Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systemscited by 234
  11. 2016Visual Storytellingcited by 176
  12. 2015The Goldilocks Principle: Reading Children's Books with Explicit Memory Representationscited by 108
12 more
  1. 2022CLIP-Event: Connecting Text and Images with Event Structurescited by 86
  2. 2018No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytellingcited by 46
  3. 2020Bringing Stories Alive: Generating Interactive Fiction Worldscited by 28
  4. 2021"Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?cited by 24
  5. 2015A Survey of Current Datasets for Vision and Language Researchcited by 13
  6. 2022Model Positionality and Computational Reflexivity: Promoting Reflexivity in Data Sciencecited by 13
  7. 2017Hierarchically-Attentive RNN for Album Summarization and Storytellingcited by 10
  8. 2018DOCK: Detecting Objects by transferring Common-sense Knowledgecited by 8
  9. 2018A Pipeline for Creative Visual Storytellingcited by 7
  10. 2021Detecting discriminatory risk through data annotation based on Bayesian inferencescited by 7
  11. 2017Applying the Wizard-of-Oz Technique to Multimodal Human-Robot Dialoguecited by 4
  12. 2017Laying Down the Yellow Brick Road: Development of a Wizard-of-Oz Interface for Collecting Human-Robot Dialoguecited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 4; 2025: 1; 2026: 1.

7 papers.