GUI-World

GUI video benchmark and training data covering six scenarios, from Android and iOS to websites and XR, with eight question types for image and video LLMs and the GUI-Vid model.

AI-assisted editorial review against a primary source. This is a catalog annotation, not an independent reproduction or endorsement.

What is this resource?

Resource type

Datasets

Environment

cross-platform

Topics

video, screen-understanding

Record publication date

Not recorded

Evidence retrieved

2026-10-16T06:40:52Z

Resource ID

github:dongping-chen/gui-world

What licenses are recorded?

Code, training data, weights, and documents can have different terms. A blank declaration means unknown, not unrestricted use.

Code

Not recorded

Data

Not recorded

Document

Not recorded

Weights

Not recorded

Dataset profile

Supervision

GUI video question answering, temporal interface understanding

Modalities

videos, frame images, text

Formats

Not recorded

Splits

train, test

Scale and counting units

• 6 GUI scenario categories — dataset taxonomy source
• 8 question types — dataset taxonomy source

Taxonomy counts describe coverage, not the number of videos or questions. Cases include Android, iOS, desktop software, websites, multi-application use, and XR. Keyframe-selection settings affect evaluation; exact sample inventories are not reported here.

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Explore related topics

Related resources

• documented by: GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding

Primary evidence and verification

Source retrieval is separate from experiment reproduction. Use the original publication or publisher page when citing claims about the resource.

1. editorial primary review

   Retrieved 2026-10-16T06:40:52Z. Supports: name, kind, summary, environments, topics, scope, relations, details.

   Content fingerprint

   d02fa5da3384a3e58cf1d28aad47497de73fe3aad0ce57219585da04fc3187ef
2. editorial primary review

   Retrieved 2026-10-17T02:03:23Z. Supports: details.dataset_profile.

   Content fingerprint

   905bf69ce80c866377841474cefe08f85ec4ef552cdd9ffeb2fb1531e07370b6
3. editorial primary review

   Retrieved 2026-10-17T02:06:30Z. Supports: details.dataset_profile.

   Content fingerprint

   d2dd5886bce90f6eaee880719c79a6ede6ec0eaa08da32d7610bde656b8dc9ed
4. editorial primary review

   Retrieved 2026-10-16T06:31:28Z. Supports: details.dataset_profile.

   Content fingerprint

   be244bfae7f89ef9449b69d85aac44295eb7b5f7e5e1bbedd76df312696676a7

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