PulseAugur
EN
LIVE 22:22:37

Video2GUI generates 12M GUI trajectories from unlabeled videos

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Video2GUI, an automated framework designed to generate large-scale interaction trajectories for training GUI agents. This system extracts data from unlabeled internet videos, converting them into structured agent trajectories through a filtering process. The resulting dataset, WildGUI, contains 12 million trajectories across over 1,500 applications, significantly improving the pre-training of models like Qwen2.5-VL and Mimo-VL. AI

IMPACT Enables creation of large-scale datasets for GUI agents, potentially improving their generalization and performance across diverse applications.

RANK_REASON Academic paper introducing a new method and dataset for GUI agent pretraining. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Video2GUI generates 12M GUI trajectories from unlabeled videos

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
Academic paper introducing a new method and dataset for GUI agent pretraining. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, product, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
124 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Hao Tian ·

    Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining

    Recent advances in multimodal large language models have driven growing interest in graphical user interface (GUI) agents, yet their generalization remains constrained by the scarcity of large-scale training data spanning diverse real-world applications. Existing datasets rely he…

RELATED ENTITIES

RELATED TOPICS