Recent progress in GUI agents has substantially improved visual grounding, yet robust planning remains challenging, particularly when the environment deviates from a canonical initial state. In real applications, users often invoke assistance mid-workflow, where software may be partially configured, steps may have been executed in different orders, or the interface may differ from its default setup. Such task-state variability is pervasive but insufficiently evaluated in existing GUI benchmarks. To address this gap, we introduce WorldGUI, a benchmark covering ten widely used desktop and web applications with tasks instantiated under diverse, systematically constructed initial states. These variations capture realistic human-computer interaction settings and enable diagnostic evaluation of an agent's ability to recover, adapt plans, and handle non-default contexts. We further present WorldGUI-Agent, a simple and model-agnostic framework that organizes planning and execution around three critique stages, improving reliability in dynamic environments. Experiments demonstrate that state-of-the-art GUI agents exhibit substantial performance degradation under non-default initial conditions, revealing limited robustness and fragile planning behaviors. Our benchmark and framework provide a foundation for developing more adaptable and reliable GUI agents. The code and data are available at https://github.com/showlab/WorldGUI.
Beyond Sequential Interaction: Benchmarking Parallel Execution and Coordination for GUI Agents
Beijing University of Posts and Telecommunications（北京邮电大学）；State Key Laboratory for General Artificial Intelligence, BIGAI（通用人工智能国家重点实验室，字节跳动公司人工智能研究院）；China University of Geosciences (Beijing)（中国地质大学（北京））；Beijing Institute of Technology（北京理工大学）
OS-Oracle: A Comprehensive Framework for Cross-Platform GUI Critic Models
Shanghai Jiaotong University（上海交通大学）；Shanghai AI Laboratory（上海人工智能实验室）；CUHK MMLab（香港大学MMLab）；The University of Hong Kong（香港大学）；The Hong Kong University of Science and Technology（香港科学与技术大学）
GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding
Huazhong University of Science and Technology（华中科技大学）；University of Notre Dame（圣母大学）；Imperial College London（伦敦帝国学院）；Peking University（北京大学）；Microsoft Research（微软研究院）；Lehigh University（理海大学）
CADWorld: Computer-Use Benchmark for Long-Horizon Computer-Aided Design
Georgia Institute of Technology（佐治亚理工学院）；North Carolina State University（北卡罗来纳州立大学）；Marquette University（马凯特大学）；Saros Lab（Saros实验室）；CAMEL-AI；National University of Singapore（新加坡国立大学）
OS-Helix: Unifying GUI Interaction and Code Execution in Native Computer-Using Agents
University of Science and Technology of China（中国科学技术大学）；Shanghai AI Laboratory（上海人工智能实验室）；National University of Singapore（新加坡国立大学）；Shanghai Jiao Tong University（上海交通大学）；Fudan University（复旦大学）；Nanjing University（南京大学）；Xi’an Jiaotong University（西安交通大学）；The University of Hong Kong（香港大学）
MacAgentBench: Benchmarking AI Agents on Real-World macOS Desktop
Shanghai Jiao Tong University（上海交通大学）；Shanghai AI Laboratory（上海人工智能实验室）；Xi’an Jiaotong University（西安交通大学）；Fudan University（复旦大学）；University of Science and Technology of China（中国科学技术大学）；Zhejiang University（浙江大学）；East China Normal University（华东师范大学）；Tsinghua University（清华大学）
提出MacAgentBench，包含676个跨25个应用的任务，采用规则评估和细粒度多检查点评分，实验表明最佳配置（OpenClaw上的Claude Opus 4.6）达到73.7% Pass@1，优势主要来自技能库而非框架设计。
UI-MOPD: Multi-Platform On-Policy Distillation for Unified GUI Agents
Tsinghua Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Xiaomi（小米）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；Zhejiang University（浙江大学）；Peng Cheng Laboratory（鹏城实验室）
ScaleWoB: Guiding GUI Agents with Coding Agents via Large-Scale Environmental Synthesis
Institute for AI Industry Research (AIR), Tsinghua University（人工智能产业研究院（AIR），清华大学）；University of Electronic Science and Technology of China（电子科技大学）；MiLM Plus, Xiaomi Inc.（小米公司MiLM Plus团队）
PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control
University of Chinese Academy of Sciences（中国科学院大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；China University of Petroleum-Beijing（中国石油大学（北京））
VisualTrap: A Stealthy Backdoor Attack on GUI Agents via Visual Grounding Manipulation
University of Science and Technology of China（中国科学技术大学）；National University of Singapore（新加坡国立大学）；East China University of Science and Technology（东华大学）
