SOURCE-LINKED INTELLIGENCE
Visual Input and Its Framing Affect Attribute-based Descriptions Produced by Large Vision-Language Models
Large vision-language models (LVLMs) are commonly used with only a single text prompt as the input, or plus an image. In this paper, we demonstrate that when the image exists, even if the text prompt is not about the specific instance (but only the concept it belongs to) in that image, the response would still be affected. For example, when the text prompt only asks for the attribute descriptions of a dog breed, an image depicting a specific dog from that breed would shift the response. Further, how the specific instance is framed in that image would determine towards which the response shifts
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T09:08:57.000Z
First collected: 2026-09-20T08:01:03.945Z. This is not the publication date.