Jigsaw: Supporting Designers to Prototype Multimodal Applications by Chaining AI Foundation Models
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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
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- 2020Language Models are Few-Shot Learnerscited by 32,199
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6 more
- 2023Shap-E: Generating Conditional 3D Implicit Functionscited by 379
- 2023AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Headcited by 264
- 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 216
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Built on by
Citing papers per year: 2024: 1; 2025: 8; 2026: 2.
11 papers.
- 2025Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Reviewcited by 16
- 2025VeriLA: A Human-Centered Evaluation Framework for Interpretable Verification of LLM Agent Failurescited by 14
- 2025Inkspire: Supporting Design Exploration with Generative AI through Analogical Sketchingcited by 13
- 2025DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Designcited by 6
- 2024Survey of User Interface Design and Interaction Techniques in Generative AI Applicationscited by 3
- 2025Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-Ozcited by 2
- 2026When LLMs Imagine People: A Human-Centered Persona Brainstorm Audit for Bias and Fairness in Creative Applicationscited by 2
- 2025AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaborationcited by 1
- 2025AIPOM: Agent-aware Interactive Planning for Multi-Agent Systemscited by 1
- 2025AI-Facilitated Episodic Future Thinking For Adults with Obesitycited by 0
- 2026Human-AI Coordination Zones: A Framework for Designing Human-in-the-Loop Experiences with Agentic AIcited by 0
- 2026Human-AI Coordination Zones: A Framework for Designing Human-in-the-Loop Experiences with Agentic AI1 May 2026
- 2026When LLMs Imagine People: A Human-Centered Persona Brainstorm Audit for Bias and Fairness in Creative Applications19 Jan 2026
- 2025Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-Oz8 Oct 2025
- 2025AIPOM: Agent-aware Interactive Planning for Multi-Agent Systems29 Sep 2025
- 2025AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration4 Aug 2025
- 2025VeriLA: A Human-Centered Evaluation Framework for Interpretable Verification of LLM Agent Failures16 Mar 2025
- 2025AI-Facilitated Episodic Future Thinking For Adults with Obesity8 Mar 2025
- 2025DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design14 Feb 2025
- 2025Inkspire: Supporting Design Exploration with Generative AI through Analogical Sketching30 Jan 2025
- 2025Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review22 Jan 2025
- 2024Survey of User Interface Design and Interaction Techniques in Generative AI Applications28 Oct 2024