README.md

metadata

license: cc-by-4.0
language:
  - en
tags:
  - art
  - design
  - agent
  - tool
configs:
  - config_name: default
    data_files:
      - split: replication
        path: replication_gt/*.jsonl
      - split: modification
        path:
          - modification_gt/task-1/*.jsonl
          - modification_gt/task-2/*.jsonl
          - modification_gt/task-3/*.jsonl

CANVAS

This repository contains the dataset accompanying the paper CANVAS: A Benchmark for Vision-Language Models on Tool-Based UI Design (AAAI 2026). CANVAS designed to evaluate a VLM's capability to generate a UI design with tool invocations in two tasks: ADesign Replication and BDesign Modification.

A. Design Replication. Single Tasks involving restoring (implementing) a given UI image as is.

B. Design Modification. Multiple Tasks involving modifying or transforming existing UIs.

Dataset Statistics

CANVAS contains 598 design tasks from 3,327 mobile UI designs across 30 categories. Each design includes an image and a JSON file representing the Figma node structure. This file organizes components (e.g., vector, text, rectangle) in a hierarchical tree with attributes like position, size, and color. AFrequency of the five most frequent UI design types, with other categories grouped. BThe distribution of node tree depth is similar across the replication and modification sets with a Gaussian-like pattern. CThe node count distribution is also similar across both sets. DThe skewed frequency of node types per design indicates common patterns in component usage.

---

Directory Structure

canvas
├── modification_gt/
│   ├── task-1/       # Attribute Modification
│   ├── task-2/       # Component Insertion
│   └── task-3/       # Mode Change
└── replication_gt/   # UI Replication

---

Modification Ground Truth (modification_gt)

Task 1: Attribute Modification

Consists of 5 sub-tasks:

• Type 1: Fill Color Adjustment (20 examples) - color_adjustment
• Type 2: Size Adjustment (20 examples) - size_adjustment
• Type 3: Text Content Change (20 examples) - text_content_change
• Type 4: Corner Radius Change (20 examples) - corner_radius_change
• Type 5: Position Adjustment (20 examples) - position_adjustment

File Structure

Each task scenario consists of a "base" and "target" file pair:

• base: UI design before modification
• target: UI design after modification

Each scenario comprises 8 files (4 for base, 4 for target):

{sub_task_type}-gid{id}-{target|base}.json       // Full Figma data
{sub_task_type}-gid{id}-{target|base}-meta.json  // Metadata
{sub_task_type}-gid{id}-{target|base}.svg        // SVG
{sub_task_type}-gid{id}-{target|base}.png        // PNG

Example: color_adjustment-gid1-base.json

Metadata Structure

Each metadata file (*-meta.json) includes:

• url: Source Figma file URL
• license: License information (typically CC BY 4.0)
• node_id: Figma node ID
• sub_task_type: Sub-task type (e.g., "color_adjustment")
• instruction: Text instruction describing the required modification

Task 2: Component Insertion

Adding a component to an existing UI.

File Structure

Each task scenario consists of a triplet of "base", "target", and "component" files:

• base: UI design before modification
• target: UI design after modification
• component: The UI component being added

Each scenario comprises 12 files (4 for base, 4 for target, 4 for component):

gid{id}-target.json      // Full Figma data
gid{id}-target-meta.json // Metadata
gid{id}-target.svg       // SVG
gid{id}-target.png       // PNG
gid{id}-base.json      // Full Figma data
gid{id}-base-meta.json // Metadata
gid{id}-base.svg       // SVG
gid{id}-base.png       // PNG
gid{id}-component.json      // Full Figma data
gid{id}-component-meta.json // Metadata
gid{id}-component.svg       // SVG
gid{id}-component.png       // PNG

Example: gid1-base.json

Metadata Structure

Each metadata file (*-meta.json) includes:

• url: Source Figma file URL
• license: License information (typically CC BY 4.0)
• node_id: Figma node ID
• instruction: Text instruction describing how to add the component

Task 3: Mode Change

Day & Night Screen State Change. Total of 100 examples (10 image groups x 10 pairs).

File Structure

Each task scenario consists of a "base" and "target" file pair:

• base: UI design before modification
• target: UI design after modification

Each scenario comprises 8 files (4 for base, 4 for target):

gid{group_id}-{subindex}-target.json      // Full Figma data
gid{group_id}-{subindex}-target-meta.json // Metadata
gid{group_id}-{subindex}-target.svg       // SVG
gid{group_id}-{subindex}-target.png       // PNG
gid{group_id}-{subindex}-base.json      // Full Figma data
gid{group_id}-{subindex}-base-meta.json // Metadata
gid{group_id}-{subindex}-base.svg       // SVG
gid{group_id}-{subindex}-base.png       // PNG

Example: gid10-1-base.json

Metadata Structure

Each metadata file (*-meta.json) includes:

• url: Source Figma file URL
• license: License information (typically CC BY 4.0)
• node_id: Figma node ID
• gid: Image group ID
• subindex: Pair index within the image group (1-10)
• instruction: Text instruction describing the required modification

---

Replication Ground Truth (replication_gt)

Tasks involving restoring (implementing) a given UI image as is. Total of 298 examples.

File Structure

In this dataset, there is no distinction between "base" and "target"; each UI design is an independent data point.

Each data point consists of 4 files:

gid{group_id}-{index}.json      // Full Figma data
gid{group_id}-{index}-meta.json // Metadata
gid{group_id}-{index}.svg       // SVG
gid{group_id}-{index}.png       // PNG

Example: gid1-5.json

Metadata Structure

Each metadata file (*-meta.json) includes:

• url: Source Figma file URL
• license: License information (typically CC BY 4.0)
• node_id: Figma node ID
• type_id: UI type ID
• type_name: UI category name (e.g., "Maps & Location")
• json_node_depth: Depth of the Figma node tree
• json_node_count: Total number of nodes
• json_node_type_count: Count by node type (FRAME, GROUP, VECTOR, TEXT, etc.)
• difficulty: Difficulty level (e.g., "standard")

BibTex

If you use this dataset, please cite:

@article{jeong2025canvas,
      title={CANVAS: A Benchmark for Vision-Language Models on Tool-Based User Interface Design}, 
      author={Daeheon Jeong and Seoyeon Byun and Kihoon Son and Dae Hyun Kim and Juho Kim},
      year={2025},
      eprint={2511.20737},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2511.20737}, 
}