Reflection with Action-Induced Visual Differences for Desktop GUI Agents

The paper introduces Evidence-First Reflection (EFR), a two-stage reflector for desktop GUI agents that separates visual difference extraction from outcome verification. EFR uses Set-of-Marks annotations to locate action sites and candidate changed regions, filters action-relevant changes, and then makes a final judgment based on cleaned evidence. Experiments on OSWorld-Verified and WindowsAgentArena show that EFR improves reflector accuracy by 7.11% and increases end-to-end task success by roughly 5–6%.

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• agents
• benchmarks
• safety