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@@ -42,7 +42,7 @@ On a more technical level, this benchmark is intended for assessing multimodal m
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  The dataset contains 1,639 samples divided into three key groups:
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- 1. **`agentbrowse` (36%)**: Pages encountered by the RunnerH agent while solving web retrieval tasks from [WebVoyager](https://arxiv.org/abs/2401.13919)
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  2. **`humanbrowse` (31.8%)**: Pages and elements interacted with by humans performing everyday tasks (e-shopping, trip planning, personal organization)
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  3. **`calendars` (32.2%)**: A specialized subset focusing on calendar interfaces, a known challenge for UI understanding models
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  The dataset contains 1,639 samples divided into three key groups:
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+ 1. **`agentbrowse` (36%)**: Pages encountered by the SurferH agent while solving web retrieval tasks from [WebVoyager](https://arxiv.org/abs/2401.13919)
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  2. **`humanbrowse` (31.8%)**: Pages and elements interacted with by humans performing everyday tasks (e-shopping, trip planning, personal organization)
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  3. **`calendars` (32.2%)**: A specialized subset focusing on calendar interfaces, a known challenge for UI understanding models
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