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Fix dataset card: declare 39 per-benchmark configs

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  1. README.md +168 -51
README.md CHANGED
@@ -19,79 +19,200 @@ tags:
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  pretty_name: "GDB: GraphicDesignBench"
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  size_categories:
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  - 1K<n<10K
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
22
  ---
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  # GDB: GraphicDesignBench
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- **A Real-World Benchmark for Graphic Design AI**
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- GDB is the first large-scale benchmark grounded in the work marketing and branding teams ship every day.
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- It provides a reproducible signal for where AI models stand on professional design tasks, and what still
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- needs to change before they can do real design work.
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-
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- - **Paper**: [arXiv:2604.04192](https://arxiv.org/abs/2604.04192)
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- - **Code**: [github.com/purvanshi/lica-bench](https://github.com/purvanshi/lica-bench)
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- - **Blog**: [lica.world/blog/gdb-real-world-benchmark-for-graphic-design](https://lica.world/blog/gdb-real-world-benchmark-for-graphic-design)
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- - **Results**: [Explore all task results](https://lica.world/blog/gdb-real-world-benchmark-for-graphic-design)
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-
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- ## Benchmark Structure
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-
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- 39 benchmarks across 7 design domains and 2 task modes (understanding + generation):
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-
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- | Domain | Understanding | Generation | Total |
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- |--------|:---:|:---:|:---:|
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- | Layout | 4 | 4 | 8 |
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- | Typography | 6 | 2 | 8 |
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- | SVG / Infographics | 5 | 3 | 8 |
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- | Template & Semantics | 3 | 2 | 5 |
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- | Animation (Temporal) | 3 | 3 | 6 |
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- | Category | 2 | 0 | 2 |
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- | Lottie | 0 | 2 | 2 |
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- | **Total** | **23** | **16** | **39** |
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  ## Usage
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  ```python
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  from datasets import load_dataset
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- # Load a specific benchmark
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  ds = load_dataset("lica-world/GDB", "svg-1")
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-
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- # Load all benchmarks
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- ds = load_dataset("lica-world/GDB", "all")
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-
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- # Load all benchmarks in a domain
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- ds = load_dataset("lica-world/GDB", "typography")
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  ```
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  ## Schema
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- Each sample contains:
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-
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  | Field | Type | Description |
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  |-------|------|-------------|
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- | `sample_id` | string | Unique sample identifier |
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- | `benchmark_id` | string | Benchmark ID (e.g., `svg-1`, `typography-3`) |
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- | `domain` | string | Domain: layout, typography, svg, template, temporal, category, lottie |
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  | `task_type` | string | `understanding` or `generation` |
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- | `benchmark_name` | string | Human-readable benchmark name |
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- | `prompt` | string | The evaluation prompt sent to the model |
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- | `ground_truth` | string | Expected answer (JSON-serialized for complex types) |
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- | `image` | Image | Input image when applicable |
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- | `media_path` | string | Relative path to media file (video, additional images) |
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- | `media_type` | string | `image`, `video`, or `none` |
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- | `metadata` | string | JSON with task-specific extra fields (SVG code, options, etc.) |
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  ## Evaluation
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- Install `lica-bench` and use the built-in evaluation pipeline:
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-
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  ```bash
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- pip install lica-bench
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  ```
92
 
93
  ```python
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- from design_benchmarks.registry import BenchmarkRegistry
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96
  registry = BenchmarkRegistry()
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  registry.discover()
@@ -99,8 +220,6 @@ bench = registry.get("svg-1")
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  scores = bench.evaluate(predictions, ground_truth)
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  ```
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102
- See the [lica-bench README](https://github.com/purvanshi/lica-bench) for full usage.
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-
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  ## Citation
105
 
106
  ```bibtex
@@ -112,6 +231,4 @@ See the [lica-bench README](https://github.com/purvanshi/lica-bench) for full us
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  }
113
  ```
114
 
115
- ## License
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-
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  Apache 2.0
 
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  pretty_name: "GDB: GraphicDesignBench"
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  size_categories:
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  - 1K<n<10K
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+ configs:
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+ - config_name: category-1
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+ data_files:
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+ - split: train
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+ path: "category-1/train-*"
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+ - config_name: category-2
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+ data_files:
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+ - split: train
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+ path: "category-2/train-*"
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+ - config_name: layout-1
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+ data_files:
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+ - split: train
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+ path: "layout-1/train-*"
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+ - config_name: layout-2
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+ data_files:
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+ - split: train
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+ path: "layout-2/train-*"
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+ - config_name: layout-3
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+ data_files:
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+ - split: train
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+ path: "layout-3/train-*"
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+ - config_name: layout-4
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+ data_files:
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+ - split: train
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+ path: "layout-4/train-*"
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+ - config_name: layout-5
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+ data_files:
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+ - split: train
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+ path: "layout-5/train-*"
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+ - config_name: layout-6
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+ data_files:
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+ - split: train
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+ path: "layout-6/train-*"
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+ - config_name: layout-7
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+ data_files:
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+ - split: train
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+ path: "layout-7/train-*"
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+ - config_name: layout-8
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+ data_files:
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+ - split: train
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+ path: "layout-8/train-*"
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+ - config_name: lottie-1
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+ data_files:
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+ - split: train
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+ path: "lottie-1/train-*"
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+ - config_name: lottie-2
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+ data_files:
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+ - split: train
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+ path: "lottie-2/train-*"
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+ - config_name: svg-1
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+ data_files:
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+ - split: train
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+ path: "svg-1/train-*"
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+ - config_name: svg-2
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+ data_files:
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+ - split: train
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+ path: "svg-2/train-*"
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+ - config_name: svg-3
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+ data_files:
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+ - split: train
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+ path: "svg-3/train-*"
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+ - config_name: svg-4
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+ data_files:
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+ - split: train
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+ path: "svg-4/train-*"
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+ - config_name: svg-5
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+ data_files:
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+ - split: train
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+ path: "svg-5/train-*"
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+ - config_name: svg-6
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+ data_files:
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+ - split: train
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+ path: "svg-6/train-*"
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+ - config_name: svg-7
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+ data_files:
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+ - split: train
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+ path: "svg-7/train-*"
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+ - config_name: svg-8
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+ data_files:
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+ - split: train
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+ path: "svg-8/train-*"
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+ - config_name: template-1
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+ data_files:
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+ - split: train
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+ path: "template-1/train-*"
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+ - config_name: template-2
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+ data_files:
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+ - split: train
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+ path: "template-2/train-*"
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+ - config_name: template-3
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+ data_files:
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+ - split: train
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+ path: "template-3/train-*"
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+ - config_name: template-4
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+ data_files:
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+ - split: train
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+ path: "template-4/train-*"
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+ - config_name: template-5
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+ data_files:
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+ - split: train
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+ path: "template-5/train-*"
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+ - config_name: temporal-1
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+ data_files:
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+ - split: train
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+ path: "temporal-1/train-*"
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+ - config_name: temporal-2
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+ data_files:
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+ - split: train
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+ path: "temporal-2/train-*"
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+ - config_name: temporal-3
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+ data_files:
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+ - split: train
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+ path: "temporal-3/train-*"
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+ - config_name: temporal-4
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+ data_files:
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+ - split: train
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+ path: "temporal-4/train-*"
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+ - config_name: temporal-5
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+ data_files:
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+ - split: train
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+ path: "temporal-5/train-*"
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+ - config_name: temporal-6
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+ data_files:
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+ - split: train
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+ path: "temporal-6/train-*"
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+ - config_name: typography-1
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+ data_files:
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+ - split: train
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+ path: "typography-1/train-*"
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+ - config_name: typography-2
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+ data_files:
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+ - split: train
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+ path: "typography-2/train-*"
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+ - config_name: typography-3
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+ data_files:
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+ - split: train
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+ path: "typography-3/train-*"
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+ - config_name: typography-4
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+ data_files:
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+ - split: train
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+ path: "typography-4/train-*"
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+ - config_name: typography-5
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+ data_files:
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+ - split: train
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+ path: "typography-5/train-*"
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+ - config_name: typography-6
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+ data_files:
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+ - split: train
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+ path: "typography-6/train-*"
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+ - config_name: typography-7
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+ data_files:
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+ - split: train
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+ path: "typography-7/train-*"
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+ - config_name: typography-8
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+ data_files:
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+ - split: train
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+ path: "typography-8/train-*"
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  ---
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181
  # GDB: GraphicDesignBench
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183
+ 39 benchmarks for evaluating vision-language models on graphic design tasks — layout, typography, SVG, template matching, animation. Built on 1,148 real design layouts from the [Lica dataset](https://lica.world).
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185
+ **Paper:** [arXiv:2604.04192](https://arxiv.org/abs/2604.04192) &nbsp;|&nbsp; **Code:** [github.com/lica-world/GDB](https://github.com/lica-world/GDB) &nbsp;|&nbsp; **Blog:** [lica.world](https://lica.world/blog/gdb-real-world-benchmark-for-graphic-design)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
186
 
187
  ## Usage
188
 
189
  ```python
190
  from datasets import load_dataset
191
 
 
192
  ds = load_dataset("lica-world/GDB", "svg-1")
 
 
 
 
 
 
193
  ```
194
 
195
  ## Schema
196
 
 
 
197
  | Field | Type | Description |
198
  |-------|------|-------------|
199
+ | `sample_id` | string | Sample identifier |
200
+ | `benchmark_id` | string | e.g. `svg-1`, `typography-3` |
201
+ | `domain` | string | layout, typography, svg, template, temporal, category, lottie |
202
  | `task_type` | string | `understanding` or `generation` |
203
+ | `prompt` | string | Evaluation prompt |
204
+ | `ground_truth` | string | Expected answer (JSON for complex types) |
205
+ | `image` | Image | Input image (when applicable) |
206
+ | `metadata` | string | Task-specific fields as JSON |
 
 
 
207
 
208
  ## Evaluation
209
 
 
 
210
  ```bash
211
+ pip install git+https://github.com/lica-world/GDB.git
212
  ```
213
 
214
  ```python
215
+ from gdb.registry import BenchmarkRegistry
216
 
217
  registry = BenchmarkRegistry()
218
  registry.discover()
 
220
  scores = bench.evaluate(predictions, ground_truth)
221
  ```
222
 
 
 
223
  ## Citation
224
 
225
  ```bibtex
 
231
  }
232
  ```
233
 
 
 
234
  Apache 2.0