UI-Venus-2 Technical Report

2026-08-27

AI Summary

本文提出UI-Venus-2，通过扩展环境覆盖、改进任务构建和增强验证机制，解决多模态GUI代理在实际应用中的可靠性问题。

Abstract

Multimodal GUI agents have emerged as a promising paradigm for digital task automation, yet transitioning from benchmark-oriented models to dependable real-world applications remains challenging due to limited environment coverage, brittle task construction, and unreliable reward verification. In this work, we present UI-Venus-2, a general-purpose foundation GUI agent designed to operate across mobile, web, and desktop environments through a unified closed-loop reasoning-action framework. To bridge the gap toward practical deployment, we jointly scale three critical dimensions: (1) Environments, expanding coverage to more than 170 multilingual mobile apps and native desktop operating systems; (2) Tasks, employing a deep-research pipeline for function-grounded instruction generation; and (3) Verification, adopting trace-level and sample-level evaluators with visual keypoints and multi-model voting to ensure reliable RL signals for training. Furthermore, we integrate safety-aware mechanisms to ensure controlled execution of consequential actions. By offering a capable, efficient, and open-source foundation, UI-Venus-2 advances the field toward more generalizable, verifiable, and self-reflective agents for real-world applications.

Problem

• Multimodal GUI agents
• digital task automation
• environment coverage
• brittle task construction
• unreliable reward verification

Innovation

• multimodal GUI agents
• unified closed-loop reasoning-action framework
• function-grounded instruction generation
• multi-model voting