Unverified50% confidenceCautionExact time
Large models perform inferential completion of image content, which in OCR tasks can lead to hallucinatory recognition—reading in characters that do not actually exist—creating a contradiction with document entry scenarios that require high fidelity.
1
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50%
Confidence
Long-term
Relevance
10/8/2026
First Seen
Sources
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Unverified开发者指出abliterate一个模型并不会让图像输出更加去审查,编码器真正价值在于提示词增强与视觉解码场景73% similarVerifiedMultimodal large models split images into fixed patches, convert them into high-dimensional vectors via a visual encoder (based on the ViT architecture), and align them to the language model's token embedding space—this is inference, not reading.73% similarUnverifiedText embeddings encode a character's visual features as high-dimensional vectors injected directly into the model, requiring no additional training and enabling faster inference, but placing higher demands on the quality and quantity of reference images.73% similarUnverified即便出现能对PR图片进行OCR扫描的安全工具,攻击者仍可通过图像混淆手段对抗基于规则的文本检测,而这些混淆对多模态大模型几乎无影响72% similar
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