| ---
|
| pretty_name: RelationGUI and RelationQA (updated release v2026.09)
|
| language:
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| - en
|
| task_categories:
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| - visual-question-answering
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| - image-to-text
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| tags:
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| - gui
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| - relational-reasoning
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| - grounding
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| - desktop
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| - mobile
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| - web
|
| size_categories:
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| - 10K<n<100K
|
| ---
|
|
|
| # RelationGUI and RelationQA
|
|
|
| Dataset resources for **Beyond element-level understanding: Explicit relational understanding for GUI agents**, *Pattern Recognition* 176 (2026), 113262.
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|
|
| [Paper](https://doi.org/10.1016/j.patcog.2026.113262) · [Code and complete release audit](https://github.com/malonghui/RelationGUI)
|
|
|
| ## Version qualification
|
|
|
| This is the **updated release v2026.09**, rebuilt and quality-filtered from the original source annotations. It is an updated dataset, rather than a recovered copy of the paper's original 37,724-sample experimental release. Mobile and web source-group counts match the paper; the historical desktop crop selection remains unverified. Filtering removes invalid annotations and excludes benchmark-source screenshots from training. Do not equate these rebuilt counts with the paper's counts or claim published performance from this release without retraining and evaluation.
|
|
|
| ## Files
|
|
|
| | File | Contents |
|
| |---|---|
|
| | `RelationGUI-cleaned.zip` | Source-group annotations, referenced screenshots, training JSONL files, full audit and exclusions |
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| | `RelationQA-cleaned.zip` | All 1,009 original questions, gold labels, original/marked/cropped images, source exclusion manifest |
|
| | `SHA256SUMS` | Archive integrity hashes |
|
|
|
| Only packaged data and its metadata belong in this repository. Training, inference and evaluation code are maintained on GitHub. Extract both archives into the same parent directory to obtain `RelationGUI/` and `RelationQA/`.
|
|
|
| ## Statistics
|
|
|
| | Platform | Accepted relation groups | Groups eligible for training |
|
| |---|---:|---:|
|
| | Desktop | 1,450 | 473 |
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| | Mobile | 20,273 | 19,761 |
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| | Web | 8,947 | 7,859 |
|
| | **Total** | **30,670** | **28,093** |
|
|
|
| Generated training files contain 75,754 grounding instructions, 75,754 referring instructions, and 84,278 relation instructions. Several instructions can derive from one source group. Relation instructions represent spatial, functional and hierarchical dimensions; these totals are not counts of independent screenshots.
|
|
|
| RelationQA retains the original **1,009 questions** across **350 source screenshots**: desktop 587, mobile 200 and web 222. Label counts: trigger 269, complement 260, parallel 230 and none 250. No new dev/test partition is introduced.
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|
|
| ## Format and use
|
|
|
| `RelationGUI/annotations.jsonl` contains stable IDs, source IDs, relative image paths, dimensions, normalized element boxes, captions, relationship annotations and explicit `train` or `benchmark_source` tags. `benchmark_source` rows document the original annotation provenance and **must not be used for training**. Use the files in `RelationGUI/train/` to avoid introducing benchmark leakage.
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|
|
| Training rows use `id`, `source_id`, `images`, `instruction` and `output`. Image paths are relative to `RelationGUI/`. Bounding boxes use `[x1, y1, x2, y2]` in `[0, 1]`.
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|
|
| `RelationQA/annotations.jsonl` contains `id`, `source_id`, `platform`, `question`, `options`, `answer` and an `images` mapping with `original`, `marked` and `crop`. These paths are relative to `RelationQA/`. The marked view uses the source's `line_img_path`; the source's `img_path` was unmarked. Evaluate exact label matches with the scorer in the GitHub repository. Gold labels are included for local evaluation and must not enter model prompts or training.
|
|
|
| ## Filtering and limitations
|
|
|
| - Correct swapped image width/height metadata in 7,210 mobile annotation files using decoded image dimensions.
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| - Exclude 1,650 groups with invalid/out-of-frame element boxes, 66 desktop groups with ambiguous group alignment, and two singleton groups.
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| - Exclude every benchmark source screenshot and exact decoded-pixel match from all training tasks.
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| - Derive grounding coordinates from original geometry; do not reuse the legacy normalization bug.
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| - Preserve original relation descriptions and labels. These automated checks do not establish new human semantic validation.
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| - Omit desktop crop augmentation and synthetic negatives whose historical inclusion is unverified.
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|
|
| The full source-hash inventory and individual exclusion records are included in the RelationGUI archive. This updated version contains no model checkpoints, API credentials, crawler scripts, or unrelated downstream datasets.
|
|
|
| Mobile imagery originates from [MobileViews](https://huggingface.co/datasets/mllmTeam/MobileViews). Desktop and web screenshots depict third-party software and websites. This card does not assign a new license to those underlying materials; their applicable terms remain in force.
|
|
|
| ## Citation
|
|
|
| ```bibtex
|
| @article{ma2026relationgui,
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| title={Beyond element-level understanding: Explicit relational understanding for GUI agents},
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| author={Ma, Longhui and Zhao, Di and Wang, Siwei and Lv, Zhao and Wang, Miao},
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| journal={Pattern Recognition},
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| volume={176},
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| pages={113262},
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| year={2026},
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| doi={10.1016/j.patcog.2026.113262}
|
| }
|
| ```
|
|
|
