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Related papers: PromptGuard: Soft Prompt-Guided Unsafe Content Mod…

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Despite the notable advancements and versatility of multi-modal diffusion models, such as text-to-image models, their susceptibility to adversarial inputs remains underexplored. Contrary to expectations, our investigations reveal that the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Xiaosen Wang , Zhijin Ge , Shaokang Wang

Text-to-Image models may generate harmful content, such as pornographic images, particularly when unsafe prompts are submitted. To address this issue, safety filters are often added on top of text-to-image models, or the models themselves…

Cryptography and Security · Computer Science 2026-01-09 Zhengyuan Jiang , Yuepeng Hu , Yuchen Yang , Yinzhi Cao , Neil Zhenqiang Gong

Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from their training data, leading to the reproduction of unsafe content such as NSFW imagery and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Renyang Liu , Kangjie Chen , Han Qiu , Jie Zhang , Kwok-Yan Lam , Tianwei Zhang , See-Kiong Ng

With the rise of text-to-image (T2I) generative AI models reaching wide audiences, it is critical to evaluate model robustness against non-obvious attacks to mitigate the generation of offensive images. By focusing on ``implicitly…

Safety filters in commercial text-to-image (T2I) models systematically block legitimate artistic content involving the human figure, treating classical nude photography with the same restrictiveness as explicit material. While prior…

Multimedia · Computer Science 2026-03-24 Luca Cazzaniga

Recently, prompt learning has emerged as the state-of-the-art (SOTA) for fair text-to-image (T2I) generation. Specifically, this approach leverages readily available reference images to learn inclusive prompts for each target Sensitive…

Computer Vision and Pattern Recognition · Computer Science 2024-10-25 Christopher T. H Teo , Milad Abdollahzadeh , Xinda Ma , Ngai-man Cheung

Large language models have gained widespread prominence, yet their vulnerability to prompt injection and other adversarial attacks remains a critical concern. This paper argues for a security-by-design AI paradigm that proactively mitigates…

Cryptography and Security · Computer Science 2025-10-02 Dalal Alharthi , Ivan Roberto Kawaminami Garcia

Large language models (LLMs) are increasingly embedded in Computer Science (CS) classrooms to automate code generation, feedback, and assessment. However, their susceptibility to adversarial or ill-intentioned prompts threatens student…

Computers and Society · Computer Science 2026-02-04 Nishat Raihan , Noah Erdachew , Jayoti Devi , Joanna C. S. Santos , Marcos Zampieri

Text-to-Image (T2I) generation is a popular AI-generated content (AIGC) technology enabling diverse and creative image synthesis. However, some outputs may contain Not Safe For Work (NSFW) content (e.g., violence), violating community…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Mingrui Liu , Sixiao Zhang , Cheng Long

While Multimodal Large Language Models (MLLMs) have made remarkable progress in vision-language reasoning, they are also more susceptible to producing harmful content compared to models that focus solely on text. Existing defensive…

Computation and Language · Computer Science 2024-12-30 Yilei Jiang , Yingshui Tan , Xiangyu Yue

The development of text-to-image (T2I) generative models, that enable the creation of high-quality synthetic images from textual prompts, has opened new frontiers in creative design and content generation. However, this paper reveals a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Zonglei Jing , Zonghao Ying , Le Wang , Siyuan Liang , Aishan Liu , Xianglong Liu , Dacheng Tao

Generative vision-language models like Stable Diffusion demonstrate remarkable capabilities in creative media synthesis, but they also pose substantial risks of producing unsafe, offensive, or culturally inappropriate content when prompted…

Artificial Intelligence · Computer Science 2025-11-18 Xin Zhao , Xiaojun Chen , Bingshan Liu , Zeyao Liu , Zhendong Zhao , Xiaoyan Gu

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of applications. Since they are highly data-driven, relying on…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Patrick Schramowski , Manuel Brack , Björn Deiseroth , Kristian Kersting

Recent progress in text-to-image (T2I) generation underscores the importance of reliable benchmarks in evaluating how accurately generated images reflect the semantics of their textual prompt. However, (1) existing benchmarks lack the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yibin Wang , Zhimin Li , Yuhang Zang , Jiazi Bu , Yujie Zhou , Yi Xin , Junjun He , Chunyu Wang , Qinglin Lu , Cheng Jin , Jiaqi Wang

Prompt engineering is an effective but labor-intensive way to control text-to-image (T2I) generative models. Its time-intensive nature and complexity have spurred the development of algorithms for automated prompt generation. However, these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Yutong He , Alexander Robey , Naoki Murata , Yiding Jiang , Joshua Nathaniel Williams , George J. Pappas , Hamed Hassani , Yuki Mitsufuji , Ruslan Salakhutdinov , J. Zico Kolter

While diffusion-based text-to-image (T2I) models provide a simple and powerful way to generate images, guiding this generation remains a challenge. For concepts that are difficult to describe through language, users may struggle to create…

Human-Computer Interaction · Computer Science 2023-08-11 John Joon Young Chung , Eytan Adar

Text-to-image diffusion models (T2I DMs) have achieved remarkable success in generating high-quality and diverse images from text prompts, yet recent studies have revealed their vulnerability to backdoor attacks. Existing attack methods…

Cryptography and Security · Computer Science 2025-08-05 Haoran Dai , Jiawen Wang , Ruo Yang , Manali Sharma , Zhonghao Liao , Yuan Hong , Binghui Wang

While text-to-image (T2I) models can synthesize high-quality images, their performance degrades significantly when prompted with novel or out-of-distribution (OOD) entities due to inherent knowledge cutoffs. We introduce World-To-Image, a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Moo Hyun Son , Jintaek Oh , Sun Bin Mun , Jaechul Roh , Sehyun Choi

Text-to-image (T2I) generation model has made significant advancements, resulting in high-quality images aligned with an input prompt. However, despite T2I generation's ability to generate fine-grained images, it still faces challenges in…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Taekyung Lee , Donggyu Lee , Myungjoo Kang
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