README.md

---
pretty_name: ScreenRef
license: other
license_name: restricted-research-only
license_link: https://huggingface.co/datasets/PrentisAI/ScreenRef-Annotations/blob/main/LICENSE
gated: true
extra_gated_eu_disallowed: true
extra_gated_heading: "Restricted access — non-commercial academic research only"
extra_gated_description: "Access requests are reviewed manually. Please allow 3–5 business days."
extra_gated_prompt: |-
  This dataset consists of screenshots of third-party websites, mobile applications, desktop environments, and frames extracted from third-party video recordings. Access is governed by the Restricted Research-Only License and Terms of Access (the LICENSE, full text: https://huggingface.co/datasets/PrentisAI/ScreenRef-Annotations/blob/main/LICENSE). If anything below differs from the LICENSE, the LICENSE prevails.

  By requesting access you agree to the LICENSE, and in particular that:

  1. you will use the dataset only for Academic Research as defined in the LICENSE: research by an individual affiliated with a university, college, or public or non-profit research institution, intended for publication, and not carried out for or on behalf of any commercial entity;
  2. you will not redistribute the dataset or any derived copy, except as the LICENSE allows (for example, storage on your institution's infrastructure for approved users only, or up to ten images in a publication with personal information redacted);
  3. you will not attempt to identify, locate, contact or profile any person whose personal information appears in the data;
  4. you understand that screenshots were captured automatically and may incidentally show personal information; you will not disseminate it, and you are asked to report it to requests@prentis.ai;
  5. any model you release that was trained on the dataset will be released only under terms that prohibit commercial use, and will cite the dataset;
  6. when notified, you will delete removed material, or all copies on termination, within 30 days;
  7. the dataset is provided "as is", without warranty, and the LICENSE is governed by the laws of the State of California.
extra_gated_fields:
  Full name: text
  Affiliation (university or public / non-profit research institution): text
  Country: country
  Institutional e-mail: text
  Intended research use: text
  I am affiliated with a university or a public or non-profit research institution, and my use is not for or on behalf of any commercial entity: checkbox
  I have read and agree to the LICENSE (Restricted Research-Only License and Terms of Access): checkbox
  I will not redistribute the data or any derived copy except as the LICENSE allows: checkbox
  I will not attempt re-identification and will not disseminate any personal information I encounter: checkbox
  I will delete data within 30 days when notified: checkbox
extra_gated_button_content: "Request access"
task_categories:
  - image-text-to-text
language:
  - en
tags:
  - gui-grounding
  - gui-agent
  - screenshot
  - abstention
size_categories:
  - 100K<n<1M
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
---

# ScreenRef

GUI grounding instructions paired with screenshots from desktop, web and mobile
environments, plus an **abstention** subset in which the referenced UI element
is *not* present and the correct behaviour is to decline to act.

> **Access to this dataset is gated and granted manually.** Use is governed by the
> [LICENSE](https://huggingface.co/datasets/PrentisAI/ScreenRef-Annotations/blob/main/LICENSE) (Restricted Research-Only License and Terms of Access): Academic
> Research only, no redistribution, no re-identification. Please read *Data provenance*
> before requesting.

The annotations, task recipes, per-image checksums and all scripts are also
available **without** access approval in
[`PrentisAI/ScreenRef-Annotations`](https://huggingface.co/datasets/PrentisAI/ScreenRef-Annotations)
(no images, 484 MB), so you can inspect the data before requesting access.

## Intended use

ScreenRef is intended for Academic Research, as defined in the LICENSE, on GUI
agents, in particular:

- training and fine-tuning models that locate a user-interface element on a desktop,
  web or mobile screenshot from a natural-language instruction (GUI grounding);
- studying abstention, i.e. declining to act when the referenced element is not on
  screen;
- analysing grounding behaviour across platforms, screen resolutions and
  instruction types.

Out of scope: any commercial use; identifying, profiling or tracking people or
accounts that appear in the screenshots; and tasks beyond single-step grounding,
such as multi-step planning, typing or scrolling, which the dataset does not
contain.

## Composition

| Subset | Instructions | Unique screenshots | Notes |
|---|---:|---:|---|
| `Crawl_*` (web / Android / Ubuntu) | 284,531 | 237,143 | screenshots captured by our own pipeline |
| `traj_*` (video-derived frames) | 326,363 | 326,363 | 1 instruction per frame |
| `*_refusal` (abstention) | 22,475 | 22,475 | correct answer is `abstain` |
| **Total** | **633,369** | **585,981** | 447 shards, ~327 GiB |

Screenshot totals by source tag:

| Tag | Screenshots | | Tag | Screenshots |
|---|---:|---|---|---:|
| `Crawl_Ubuntu` | 100,761 | | `traj_parallel` | 170,983 |
| `Crawl_1M_filter` | 92,919 | | `traj_mr` | 76,799 |
| `Crawl_Android_part1` | 43,463 | | `traj_hr` | 65,858 |
| `refusal_parallel` | 16,872 | | `traj_endfix` | 12,723 |
| `refusal_hr` | 4,095 | | `refusal_endfix` | 1,508 |

58 task groups in total. Because some screenshots carry several instructions,
there are 8.1% more rows than unique images (all re-use is within `Crawl_*`;
`traj_*` and the refusal subset are strictly 1 : 1).

## Schema

| Column | Type | Description |
|---|---|---|
| `image` | `Image()` | the screenshot |
| `width`, `height` | `int32` | native resolution of the screenshot |
| `conversations` | `string` | JSON list of `{"from": "human"/"gpt", "value": ...}` |
| `task` | `string` | task group the row belongs to |
| `conv_style` | `string` | conversation template identifier |

`conversations` is stored as a raw JSON string and is **not** re-interpreted by
the loader. Coordinates are **integers normalized to a 1000 × 1000 space**, not
pixels — for tool-call `coordinate` and `<box>` alike. To get pixels:
`x_px = x / 1000 * width`, `y_px = y / 1000 * height`.

### Action space

Answers are `<tool_call>` blocks. The tool name follows the platform and the
action distinguishes grounding from abstention:

| Platform | Tool | Grounding action | Abstention action |
|---|---|---|---|
| desktop | `computer_use` | `left_click` + `coordinate` | `abstain` |
| web | `browser_use` | `left_click` + `coordinate` | `abstain` |
| mobile | `mobile_use` | `click` + `coordinate` | `abstain` |

Row counts: `left_click` 541,793 · `click` 58,782 · `abstain` 22,475. The three
`*_text_box` tasks (10,319 rows) answer with `<ref>…</ref><box>[[x1,y1,x2,y2]]</box>`
instead of a tool call. There are no typing, scrolling, dragging or keyboard actions.

Example of an abstention row:

```json
{"from": "human", "value": "<image>\nLocate and click the \"Window\" menu item."}
{"from": "gpt",   "value": "<tool_call>\n{\"name\": \"computer_use\", \"arguments\": {\"action\": \"abstain\"}}\n</tool_call>"}
```

## Usage

```python
from datasets import load_dataset

ds = load_dataset("PrentisAI/ScreenRef", split="train", streaming=True)  # requires access + token
row = next(iter(ds))
row["image"]          # PIL image
row["task"]           # e.g. "traj_desktop_refusal__hr"
```

Every shard holds rows from exactly one task, and `shard_index.tsv` lists the
task, row count and size of each shard. To work with a subset, download only
its shards instead of filtering the full 327 GiB. For example, abstention rows
only:

```python
import csv
from datasets import load_dataset

# get shard_index.tsv first, e.g. hf_hub_download("PrentisAI/ScreenRef", "shard_index.tsv", repo_type="dataset")
rows = csv.DictReader(open("shard_index.tsv"), delimiter="\t")
shards = [r["shard"] for r in rows if "refusal" in r["task"]]   # 12 shards, 5.8 GiB

refusal = load_dataset("PrentisAI/ScreenRef", data_files=shards, split="train")  # 22,475 rows
```

## Data provenance

The two halves of the dataset were obtained differently, but in both cases **the
content shown on screen belongs to third parties**, not to the maintainers.
Specifically:

- **`Crawl_*`** — screenshots collected by the maintainers with their own
  automated pipeline: publicly reachable web pages rendered in a browser, Android
  applications running in an emulator (1080×2400) and Ubuntu desktop applications
  running in a virtual machine (1920×1080). They are not copied from any existing
  public dataset. `Crawl_1M_filter` covers a long tail of websites (577
  distinct domains appear in the annotation text alone, 72% of them only once,
  spanning `.com/.io/.org/.gov/.de/.ru/.dev/.edu` and others).
- **`traj_*` and the refusal subset** — frames extracted from publicly available
  YouTube tutorial videos of software being operated. The directory name in each
  image path is the source video's YouTube ID.

Rights in the depicted websites, applications, user interfaces and video
recordings remain with their respective owners. The maintainers make no claim
of ownership over that content. Prentis AI owns only the annotations and the
compilation; the LICENSE licenses those and sets the terms of access for the
screenshots.

**Takedown / rights requests:** if you are a rights holder and wish content
removed, contact the maintainers (see *Contact*). Removal requests are actioned
and a corrected revision published; access may be suspended meanwhile.

Because screenshots were captured automatically, some may incidentally show
personal information. Please report any you encounter to the address under
*Contact*.

## Known limitations

- **Instruction verb and action can disagree.** Every grounding answer is a single
  click, but about 3.6% of the video-derived instructions name a different gesture —
  right-click (5,960), double-click (3,659), hover (1,650), drag (277) or long-press
  (223). Treat these as location supervision only; the dataset does not teach
  gesture selection.
- Coordinates are normalized to 0–1000 on both axes, while resolutions are
  heterogeneous (1080×2400, 1920×1080, 2560×1440, 3840×2160 and others); convert
  with `width` / `height` if you need pixels.

## Licence

See the [LICENSE](https://huggingface.co/datasets/PrentisAI/ScreenRef-Annotations/blob/main/LICENSE) (the same file is included here and, publicly, in the annotation repository). In short: Academic Research only (as defined there), no
commercial use, no redistribution beyond the listed exceptions, no
re-identification, and deletion within 30 days of notice. Models trained on the
dataset may be released under non-commercial terms. The LICENSE grants no rights in
the depicted software, web content or recorded material.

## Contact

Access review, personal-information reports and takedown requests:
**requests@prentis.ai**

## Citation

The accompanying paper is currently under review. Citation information will be
added upon publication.