mlsanityData to 7 Oct 2026

Jigsaw: Supporting Designers to Prototype Multimodal Applications by Chaining AI Foundation Models

arXiv 2310.08574 ↗First posted 12 Oct 2023cs.HC cs.AI cs.LGcited by 11

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Abstract (arXiv)

Recent advancements in AI foundation models have made it possible for them to be utilized off-the-shelf for creative tasks, including ideating design concepts or generating visual prototypes. However, integrating these models into the creative process can be challenging as they often exist as standalone applications tailored to specific tasks. To address this challenge, we introduce Jigsaw, a prototype system that employs puzzle pieces as metaphors to represent foundation models. Jigsaw allows designers to combine different foundation model capabilities across various modalities by assembling compatible puzzle pieces. To inform the design of Jigsaw, we interviewed ten designers and distilled design goals. In a user study, we showed that Jigsaw enhanced designers' understanding of available foundation model capabilities, provided guidance on combining capabilities across different modalities and tasks, and served as a canvas to support design exploration, prototyping, and documentation.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 18 of its 51 references that are in the map. First posted on arXiv 12 Oct 2023.

Builds on

18 of 51 references.

References · 18

  1. 2017Attention Is All You Needcited by 59,932
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
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  8. 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,054
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  12. 2022Socratic Models: Composing Zero-Shot Multimodal Reasoning with Languagecited by 513
6 more
  1. 2023Shap-E: Generating Conditional 3D Implicit Functionscited by 379
  2. 2023AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Headcited by 264
  3. 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 216
  4. 2022PromptChainer: Chaining Large Language Model Prompts through Visual Programmingcited by 134
  5. 2021Towards A Process Model for Co-Creating AI Experiencescited by 18
  6. 2023Exploring Challenges and Opportunities to Support Designers in Learning to Co-create with AI-based Manufacturing Design Toolscited by 16

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 8; 2026: 2.

11 papers.