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Oct 12 · Monday

All papers

Found 2 papers
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Attack type

Jailbreaks48Prompt injection12Poisoning and backdoors8Model tampering1Extraction and theft7Detection evasion8Malicious use1

System component

Fine-tuning and open weights4Multimodal2
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Attack type：Model tamperingAttack type：Malicious useSystem component：MultimodalClear all

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  2. AttacksarXiv 2601.12983

    ChartAttack：测试大语言模型在图表生成中对恶意提示的脆弱性

    提出 ChartAttack，用恶意提示驱动代码模型生成误导图表

    arXiv
    2601.12983
    Published
    Layer
    Prompt layer
    Setting
    Models and APIs
    Evaluated models
    Claude-4.6-Sonnet, GPT-4o, Gemini-2.5-Flash and others20
    AbstractChartAttack 生成不改数据的误导图，降低 MLLM 与人类的图表问答准确率。

    ChartAttack 研究恶意提示能否让 MLLM 在不改数据的情况下生成误导图表，并量化这些图对其他 MLLM 和人类图表问答的影响。

    Paper analysisRead analysis
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