| --- |
| pretty_name: ContrastGround |
| configs: |
| - config_name: corpus |
| data_files: |
| - split: train |
| path: data/corpus/train.jsonl |
| - config_name: selectground-8b |
| data_files: |
| - split: train_pairs |
| path: data/selectground-8b/train_pairs.jsonl |
| - split: train_replay |
| path: data/selectground-8b/train_replays.jsonl |
| - config_name: selectground-30b-a3b |
| data_files: |
| - split: train_pairs |
| path: data/selectground-30b-a3b/train_pairs.jsonl |
| - split: train_replay |
| path: data/selectground-30b-a3b/train_replays.jsonl |
| task_categories: |
| - image-to-text |
| tags: |
| - gui-grounding |
| - computer-use |
| - contrastive-learning |
| - sft |
| license: other |
| --- |
| |
| # ContrastGround |
|
|
| ContrastGround is the training corpus for the updated SelectGround-8B and |
| SelectGround-30B-A3B checkpoints. It combines UI-Vision-cleaned ClickContrast |
| examples with teacher-verified hard negatives mined from GroundCUA. It does not |
| contain UI-Vision examples. |
|
|
| ## Which configuration should I use? |
|
|
| | Configuration | Pair rows | Replay rows | Released model | |
| |---|---:|---:|---| |
| | `selectground-8b` | 4,942 | 4,103 | `ruotian/SelectGround-8B` | |
| | `selectground-30b-a3b` | 4,544 | 3,824 | `ruotian/SelectGround-30B-A3B` | |
| | `corpus` | 4,944 | 4,103 | Auditable union of both recipes | |
|
|
| The two model configurations are intentionally different. Use the exact |
| configuration named by the model card to reproduce that checkpoint. The |
| `corpus` rows include `training_configs`, which records membership in one or |
| both released recipes. |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("ruotian/ContrastGround", "selectground-8b") |
| pairs = dataset["train_pairs"] |
| replay = dataset["train_replay"] |
| ``` |
|
|
| The `image` field is a repository-relative content-addressed path. When using a |
| snapshot checkout, resolve it relative to the snapshot root. |
|
|
| ## Schema |
|
|
| Every row contains `image`, `image_width`, `image_height`, `instruction`, |
| `response`, `target_bbox`, `source_ref`, `role`, and `source_license`. Pair rows |
| also contain `distractor_bbox` and `candidate_bboxes`, which supervise the |
| SelectGround auxiliary selection loss. Coordinates in bounding boxes are |
| absolute source-image pixels; `response` is the target center in normalized |
| 0–1000 coordinates. |
|
|
| ## Construction |
|
|
| The ClickContrast component starts from Click-100k and removes all examples |
| whose canonical source is UI-Vision (`element_grounding` or |
| `layout_grounding`). Its replay remains stratified across the retained |
| Click-100k sources. |
|
|
| The GroundCUA component uses two natural-language views per target. A target is |
| eligible only when MAI-UI-8B and UI-Venus-1.5-8B both land inside the original |
| pixel-space ground-truth box, while Qwen3-VL-8B misses the expanded target |
| neighborhood and lands on a different native UI element. Spatial prompts also |
| require a unique text anchor and an unambiguous nearest target. The released |
| views differ only in how conservatively those GroundCUA pairs and replay rows |
| are sampled. |
|
|
| Pinned upstream revisions and SHA-256 checksums for every JSONL are recorded in |
| `manifest.json`. Images are named by their byte-level SHA-256 digest; 8,423 |
| source paths collapse to 6,834 distinct image files. |
|
|
| ## Licensing and provenance |
|
|
| GroundCUA is distributed under MIT by ServiceNow. At the pinned revision used |
| here, the Click-100k dataset card does not declare a dataset-level license. |
| Accordingly this mixed-source dataset uses `license: other`, and every row |
| records its source and source-license status. Users are responsible for |
| checking the upstream terms for their intended use. This card does not |
| relicense upstream images or annotations. |
|
|
| The optional teacher-point provenance fields inside `source_ref` are |
| JSON-encoded coordinate strings so that Click-100k and GroundCUA rows share a |
| stable Arrow schema; they are not training targets. |
|
|
| ## Evaluation leakage |
|
|
| The ClickContrast component was rebuilt to exclude UI-Vision provenance before |
| training. ScreenSpot-Pro, UI-Vision, and OSWorld-G are not validation splits of |
| this dataset. Reported released checkpoints were selected using those public |
| benchmarks, so their scores should be treated as test-tuned rather than as |
| held-out model-selection estimates. |
|
|
