--- license: apache-2.0 language: - en tags: - accessibility - gui - ui-understanding - vision-language - macos - silver-dataset - pseudo-labels - distillation task_categories: - image-to-text - visual-question-answering size_categories: - 1K 🔗 **Source dataset:** [macpaw-research/Screen2AX-Tree](https://huggingface.co/datasets/macpaw-research/Screen2AX-Tree) (Apache-2.0). > Screenshots and ground-truth trees are redistributed from there unchanged; the predicted > trees and generation metadata are the only new fields in this dataset. Each sample contains the original screenshot, the human-curated ground-truth AX tree from Screen2AX-Tree, and the AX tree predicted by Qwen3-VL-235B from the screenshot alone. The dataset is intended for **knowledge distillation** of smaller vision-language models on the Screen2AX accessibility-tree generation task, and as a reference output for studying the failure modes of large frontier VLMs on macOS GUI understanding. > ⚠️ **This is a silver dataset.** The `ax_tree_pred` field is a model output, not a > verified label. Quality is not human-checked; treat it as a noisy supervision signal. > The `ax_tree_gt` field carries the original Screen2AX-Tree ground truth and is the > only field suitable as a clean reference. ## Dataset structure A single split with all **1127** samples from the original Screen2AX-Tree (the upstream 85 / 15 train/val split is not preserved here — define your own if you need one). ### Fields | Field | Type | Description | |---------------------|----------|--------------------------------------------------------------------------| | `id` | string | Sample id (matches Screen2AX-Tree filename, e.g. `"0"` ⇒ `0.png`). | | `image` | image | macOS application screenshot (Retina, 2× logical resolution). | | `image_width` | int | Image width in pixels. | | `image_height` | int | Image height in pixels. | | `ax_tree_gt` | string | Ground-truth linearized AX tree (from Screen2AX-Tree). | | `ax_tree_pred` | string | Qwen3-VL-235B predicted AX tree. | | `model` | string | Generator model id (`Qwen/Qwen3-VL-235B-A22B-Instruct`). | | `temperature` | float | Sampling temperature used (`0.0`). | | `max_tokens` | int | Generation cap (`8192`). | | `prompt_tokens` | int | Prompt token count for this sample. | | `completion_tokens` | int | Generated token count for this sample. | | `latency_seconds` | float | Wall-clock generation latency. | | `node_count` | int | Number of nodes in the predicted tree. | | `parse_success` | bool | Whether `ax_tree_pred` parsed cleanly into a tree. | ### AX tree format Each line is one UI element; 2-space indentation encodes the parent-child hierarchy: ``` Role(subrole) [x1,y1,x2,y2] key1="value1" key2="value2" ``` - `Role` — accessibility role with `AX` prefix retained (`AXButton`, `AXStaticText`, ...). - `(subrole)` — optional subrole (`standard window`, `close button`, `switch`, ...). - `[x1,y1,x2,y2]` — bounding box, normalized to a `0–1000` range (top-left / bottom-right). - Attributes are included only when present: `name="..."`, `desc="..."`, `value="..."`. Example: ``` AXWindow(standard window) [101,38,1101,1038] name="App" AXToolbar [0,0,1000,60] AXButton [10,15,40,45] name="Save" ``` ## Generation procedure - **Model:** [`Qwen/Qwen3-VL-235B-A22B-Instruct`](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct), served via vLLM (OpenAI-compatible API). - **Decoding:** `temperature=0.0`, `max_tokens=8192`. - **Input:** the raw screenshot at native (Retina) resolution. - **Prompting:** zero-shot. The full system prompt enumerates the valid AX roles and the required output grammar; the user message is `"Generate the complete accessibility tree for this screenshot."` Every sample uses an identical prompt — no few-shot examples, no CoT, no tool use. - **Post-processing:** Markdown code-fence stripping only. Trees that fail to parse are retained verbatim and flagged via `parse_success=false`. ## Loading ```python from datasets import load_dataset ds = load_dataset("proc1v/screen2ax-tree-silver-qwen3vl-235b", split="train") print(ds) ex = ds[0] ex["image"].show() print(ex["ax_tree_pred"]) ``` ## Intended uses - **Distillation / pseudo-label SFT** of smaller VLMs (e.g. Qwen2-VL-7B, Qwen2.5-VL-7B, ShowUI) on macOS accessibility-tree generation. - **Error analysis** of frontier-scale VLMs on hierarchical GUI understanding. - **Benchmark warm-up data** when full Screen2AX-Tree is not enough — silver labels cover the same screenshots; the ground-truth labels live in `ax_tree_gt`. ### Out-of-scope uses - Reporting absolute model performance: `ax_tree_pred` is a noisy signal; use `ax_tree_gt` for evaluation. - Production accessibility tooling: the predicted trees have not been validated by humans and are unsuitable for assistive-technology end users. ## Limitations and known issues - **Coordinate scaling.** Screenshots are 2× Retina (logical macOS points × 2); the `0–1000` bbox range is normalized to image dimensions. Convert to pixels by multiplying by `image_width / 1000` and `image_height / 1000`. - **Generator quality is mixed.** Even a 235B-parameter model under-recalls deep trees — many predictions miss subtrees, hallucinate roles, or flatten hierarchies. Filter on `node_count` or `parse_success` if needed. - **Truncation.** Some predictions hit `max_tokens=8192` and were cut off mid-tree. - **Surrogate codepoints** in the original Screen2AX-Tree have been stripped from text values during linearization to keep the dataset Arrow/Parquet-safe. ## Source dataset and license Derived from [`macpaw-research/Screen2AX-Tree`](https://huggingface.co/datasets/macpaw-research/Screen2AX-Tree) (Apache-2.0). Screenshots and `ax_tree_gt` are redistributed unchanged under the same license. The `ax_tree_pred` field and other generation metadata are released under Apache-2.0 by the dataset author. If you use this dataset, please also acknowledge the original Screen2AX work and the generator model: - **Screen2AX-Tree** — [`macpaw-research/Screen2AX-Tree`](https://huggingface.co/datasets/macpaw-research/Screen2AX-Tree) - **Qwen3-VL** — [`Qwen/Qwen3-VL-235B-A22B-Instruct`](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct)