EvoGUI: An Evolution-Aware Benchmark for GUI State-Transition Understanding

• URL: http://arxiv.org/abs/2607.17050v1
• Date: Sun, 19 Jul 2026 03:29:08 GMT
• Title: EvoGUI: An Evolution-Aware Benchmark for GUI State-Transition Understanding
• Abstract summary: EvoGUI is a framework that converts normalized GUI trajectories into three complementary visual question answering probes.<n>We instantiate EvoGUI-Bench from Mind2Web and WebLINX, yielding 3,000 instances across 120 domains.<n>The strongest model reaches only 60.4 EvoGain, while model scale and GUI specialization do not reliably predict performance.
• Score: 54.222234064832
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: GUI agents must reason about how actions transform interface states, but end-to-end success rates entangle this ability with perception, grounding, planning, and recovery. We introduce EvoGUI, a diagnostic framework that converts normalized GUI trajectories into three complementary visual question answering probes: temporal ordering, inverse action/value prediction, and contrastive one-step successor discrimination. Their labels are derived from trajectory order and logged actions, requiring no additional task-label annotation after trajectory normalization. We instantiate EvoGUI-Bench from Mind2Web and WebLINX, yielding 3,000 instances across 120 domains, and evaluate 28 vision-language model configurations zero-shot. The strongest model reaches only 60.4 EvoGain, while model scale and GUI specialization do not reliably predict performance. These results establish EvoGUI-Bench as a scalable diagnostic complement to end-to-end GUI-agent evaluation while exposing substantial headroom in state-transition understanding. The source code is publicly available at https://github.com/Yyhhh6/EvoGUI.

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