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index.html

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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>VLSBench: Unveiling Information Leakage in Multimodal Safety</title>
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<link rel="icon" href="./static/images/logo.png">
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<link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro" rel="stylesheet">
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<img src="static/images/leaderbord_paper.png" alt="pipeline" width="75%"/>
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<img src="static/images/leaderbord_paper.png" alt="pipeline" width="60%"/>
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<p>
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We evaluate various MLLMs including open-source models and close-source APIs. We also benchmark several safety aligned baselines. The evaluation is conducted by GPT-4o with a specialized prompt. We classify the response into three type, safe with refusal, safe with warning and unsafe. The safe rate is sum of safe refuse rate and safe warning rate.
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</p>

static/images/logo.png

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