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@@ -60,7 +60,7 @@ Dataset for the paper: [WebUIBench: A Comprehensive Benchmark for Evaluating Mul
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  ## Introduction
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- ![Task overview of WebUIBench from the WebUI Perception, HTML Programming, WebUI-HTML Understanding subtask and WebUI-to-Code task](https://raw.githubusercontent.com/MAIL-Tele-AI/WebUIBench/blob/main/imgs/overview.png)
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  we introduce WebUIBench, a large-scale and comprehensive benchmark designed to evaluate the WebUI-to-Code capabilities of Multimodal Large Language Models (MLLMs). WebUIBench comprises over **21K question-answer pairs** derived from more than **0.7K real-world websites**, encompassing **9 distinct subtasks**. We conducted extensive experiments on 7 state-of-the-art closed-source and 22 prominent open-source MLLMs. Our key findings highlight the models' deficiencies in webpage generation tasks across various dimensions, including cross-modality reasoning, element localization, and webpage layout generation.
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  ## Introduction
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+ ![Task overview of WebUIBench from the WebUI Perception, HTML Programming, WebUI-HTML Understanding subtask and WebUI-to-Code task](https://github.com/MAIL-Tele-AI/WebUIBench/blob/main/imgs/overview.png)
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  we introduce WebUIBench, a large-scale and comprehensive benchmark designed to evaluate the WebUI-to-Code capabilities of Multimodal Large Language Models (MLLMs). WebUIBench comprises over **21K question-answer pairs** derived from more than **0.7K real-world websites**, encompassing **9 distinct subtasks**. We conducted extensive experiments on 7 state-of-the-art closed-source and 22 prominent open-source MLLMs. Our key findings highlight the models' deficiencies in webpage generation tasks across various dimensions, including cross-modality reasoning, element localization, and webpage layout generation.
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