Release updated v2026.09 datasets with quality filtering and benchmark isolation

README.md

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----
-license: apache-2.0
----
+---
+pretty_name: RelationGUI and RelationQA (updated release v2026.09)
+language:
+- en
+task_categories:
+- visual-question-answering
+- image-to-text
+tags:
+- gui
+- relational-reasoning
+- grounding
+- desktop
+- mobile
+- web
+size_categories:
+- 10K<n<100K
+---
+
+# RelationGUI and RelationQA
+
+Dataset resources for **Beyond element-level understanding: Explicit relational understanding for GUI agents**, *Pattern Recognition* 176 (2026), 113262.
+
+[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 |
+| `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 |
+| Mobile | 20,273 | 19,761 |
+| 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.
+
+## 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.
+
+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]`.
+
+`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.
+- Exclude 1,650 groups with invalid/out-of-frame element boxes, 66 desktop groups with ambiguous group alignment, and two singleton groups.
+- Exclude every benchmark source screenshot and exact decoded-pixel match from all training tasks.
+- Derive grounding coordinates from original geometry; do not reuse the legacy normalization bug.
+- Preserve original relation descriptions and labels. These automated checks do not establish new human semantic validation.
+- Omit desktop crop augmentation and synthetic negatives whose historical inclusion is unverified.
+
+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,
+  title={Beyond element-level understanding: Explicit relational understanding for GUI agents},
+  author={Ma, Longhui and Zhao, Di and Wang, Siwei and Lv, Zhao and Wang, Miao},
+  journal={Pattern Recognition},
+  volume={176},
+  pages={113262},
+  year={2026},
+  doi={10.1016/j.patcog.2026.113262}
+}
+```

RelationGUI-cleaned.zip

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+size 2658426934

RelationQA-cleaned.zip

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SHA256SUMS

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+743348bc8d08e0018b1ec2e76002023183f2bd24fe300d83f39765229d1fab79  RelationQA-cleaned.zip