AutoGUIWorld: Image Generators as Visual World Models for GUI Agent

arXiv:2610.01215 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Code: https://github.com/ImYangC7/AutoGUIWorld

Terminology

• Grounding — 48× in this paper · explained in 3 episodes
• Benchmark — 29× in this paper · explained in 2 episodes
• World Model — 26× in this paper · explained in 7 episodes
• Accuracy — 13× in this paper · explained in 1 episode
• Alignment — 10× in this paper · explained in 1 episode
• Fidelity — 10× in this paper · explained in 2 episodes
• AUC — 9× in this paper · explained in 2 episodes
• Action Space — 9× in this paper · explained in 1 episode
• Benchmarking — 5× in this paper · explained in 3 episodes
• Aggregation — 4× in this paper · explained in 1 episode
• Windows Agent Arena — 4× in this paper
• Consistency — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Task Planning — 2× in this paper · explained in 2 episodes
• Verifier — 2× in this paper · explained in 2 episodes
• Visual Grounding — 2× in this paper · explained in 2 episodes
• Action Flow — 1× in this paper · explained in 1 episode
• Agent Harness — 1× in this paper · explained in 2 episodes
• Agentic Task — 1× in this paper · explained in 1 episode
• Agentic Tasks — 1× in this paper · explained in 1 episode
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Human-in-the-Loop — 1× in this paper · explained in 3 episodes
• Latent Dynamics — 1× in this paper · explained in 2 episodes
• Partially observable Markov decision process (POMDP) — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Gym-Anything: Turn any Software into an Agent Environment
• ProSoftArena: Benchmarking Hierarchical Capabilities of Multimodal Agents in Professional Software Environments
• Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
• MobileDreamer: Generative Sketch World Model for GUI Agent
• Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation
• General Agentic Planning Through Simulative Reasoning with World Models
• Mind2Web: Towards a Generalist Agent for the Web
• DynaWeb: Model-Based Reinforcement Learning of Web Agents
• CADWorld: Computer-Use Benchmark for Long-Horizon Computer-Aided Design
• CWM: An Open-Weights LLM for Research on Code Generation with World Models
• SEE: Structure-aware Exploring \& Exploiting for Long-horizon GUI Agent Trajectory Synthesis
• WebEvolver: Enhancing Web Agent Self-Improvement with Coevolving World Model
• GUI-CC: Benchmarking Contextual Consistency of GUI World Models as Agent Environments
• Image Generators are Generalist Vision Learners
• Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents
• Computer-Using World Model
• WebSTAR: Scalable Data Synthesis for Computer Use Agents with Step-Level Filtering
• Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents
• TreeCUA: Efficiently Scaling GUI Automation with Tree-Structured Verifiable Evolution
• Learning with Challenges: Adaptive Difficulty-Aware Data Generation for Mobile GUI Agent Training

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