Scout: Rapid Exploration of Interface Layout Alternatives through High-Level Design Constraints
Not on the map. Why?
Abstract (arXiv)
Although exploring alternatives is fundamental to creating better interface designs, current processes for creating alternatives are generally manual, limiting the alternatives a designer can explore. We present Scout, a system that helps designers rapidly explore alternatives through mixed-initiative interaction with high-level constraints and design feedback. Prior constraint-based layout systems use low-level spatial constraints and generally produce a single design. Tosupport designer exploration of alternatives, Scout introduces high-level constraints based on design concepts (e.g.,~semantic structure, emphasis, order) and formalizes them into low-level spatial constraints that a solver uses to generate potential layouts. In an evaluation with 18 interface designers, we found that Scout: (1) helps designers create more spatially diverse layouts with similar quality to those created with a baseline tool and (2) can help designers avoid a linear design process and quickly ideate layouts they do not believe they would have thought of on their own.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jan 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 5; 2025: 3.
11 papers.
- 2024UICoder: Finetuning Large Language Models to Generate User Interface Code through Automated Feedbackcited by 26
- 2024UIClip: A Data-driven Model for Assessing User Interface Designcited by 14
- 2024VRCopilot: Authoring 3D Layouts with Generative AI Models in VRcited by 10
- 2022Predicting and Explaining Mobile UI Tappability with Vision Modeling and Saliency Analysiscited by 9
- 2024Graph4GUI: Graph Neural Networks for Representing Graphical User Interfacescited by 6
- 2023DiLogics: Creating Web Automation Programs With Diverse Logicscited by 5
- 2025DuetUI: A Bidirectional Context Loop for Human-Agent Co-Generation of Task-Oriented Interfacescited by 3
- 2021Semantic Snapping for Guided Multi-View Visualization Designcited by 0
- 2024From Metrics to Meaning: Time to Rethink Evaluation in Human-AI Collaborative Designcited by 0
- 2025ControlGUI: Guiding Generative GUI Exploration through Perceptual Visual Flowcited by 0
- 2025StructLayoutFormer:Conditional Structured Layout Generation via Structure Serialization and Disentanglementcited by 0
- 2025StructLayoutFormer:Conditional Structured Layout Generation via Structure Serialization and Disentanglement30 Oct 2025
- 2025DuetUI: A Bidirectional Context Loop for Human-Agent Co-Generation of Task-Oriented Interfaces16 Sep 2025
- 2025ControlGUI: Guiding Generative GUI Exploration through Perceptual Visual Flow5 Feb 2025
- 2024VRCopilot: Authoring 3D Layouts with Generative AI Models in VR18 Aug 2024
- 2024UICoder: Finetuning Large Language Models to Generate User Interface Code through Automated Feedback11 Jun 2024
- 2024Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces21 Apr 2024
- 2024UIClip: A Data-driven Model for Assessing User Interface Design18 Apr 2024
- 2024From Metrics to Meaning: Time to Rethink Evaluation in Human-AI Collaborative Design30 Jan 2024
- 2023DiLogics: Creating Web Automation Programs With Diverse Logics10 Aug 2023
- 2022Predicting and Explaining Mobile UI Tappability with Vision Modeling and Saliency Analysis5 Apr 2022
- 2021Semantic Snapping for Guided Multi-View Visualization Design17 Sep 2021