Black Box Adversarial Prompting for Foundation Models

Prompting interfaces allow users to quickly adjust the output of generative models in both vision and language. However, small changes and design choices in the prompt can lead to significant differences in the output. In this work, we develop a black-box framework for generating adversarial prompts...

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Bibliographic Details
Main Authors Maus, Natalie, Chao, Patrick, Wong, Eric, Gardner, Jacob
Format Journal Article
LanguageEnglish
Published 08.02.2023
Subjects
Computer Science - Learning
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Summary:Prompting interfaces allow users to quickly adjust the output of generative models in both vision and language. However, small changes and design choices in the prompt can lead to significant differences in the output. In this work, we develop a black-box framework for generating adversarial prompts for unstructured image and text generation. These prompts, which can be standalone or prepended to benign prompts, induce specific behaviors into the generative process, such as generating images of a particular object or generating high perplexity text.
DOI:10.48550/arxiv.2302.04237