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The practical use of text-to-image generation has evolved from simple, monolithic models to complex workflows that combine multiple specialized components. While workflow-based approaches can lead to improved image quality, crafting…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Rinon Gal , Adi Haviv , Yuval Alaluf , Amit H. Bermano , Daniel Cohen-Or , Gal Chechik

Image content safety has become a significant challenge with the rise of visual media on online platforms. Meanwhile, in the age of AI-generated content (AIGC), many image generation models are capable of producing harmful content, such as…

Large Language Models (LLMs) are redefining offensive cybersecurity by allowing the generation of harmful machine code with minimal human intervention. While attackers take advantage of dark LLMs such as XXXGPT and WolfGPT to produce…

Cryptography and Security · Computer Science 2026-04-14 Ricardo Bessa , Rui Claro , João Trindade , João Lourenço

Text-to-image models have made significant strides, producing impressive results in generating images from textual descriptions. However, creating a scalable pipeline for deploying these models in production remains a challenge. Achieving…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Parmida Atighehchian , Henry Wang , Andrei Kapustin , Boris Lerner , Tiancheng Jiang , Taylor Jensen , Negin Sokhandan

In recent years Generative Machine Learning systems have advanced significantly. A current wave of generative systems use text prompts to create complex imagery, video, even 3D datasets. The creators of these systems claim a revolution in…

Computers and Society · Computer Science 2023-02-03 Jon McCormack , Camilo Cruz Gambardella , Nina Rajcic , Stephen James Krol , Maria Teresa Llano , Meng Yang

While Large Language Models (LLMs) are widely used, they remain susceptible to jailbreak prompts that can elicit harmful or inappropriate responses. This paper introduces STAR-Teaming, a novel black-box framework for automated red teaming…

Computation and Language · Computer Science 2026-04-22 MinJae Jung , YongTaek Lim , Chaeyun Kim , Junghwan Kim , Kihyun Kim , Minwoo Kim

As large language models (LLMs) become increasingly capable, security and safety evaluation are crucial. While current red teaming approaches have made strides in assessing LLM vulnerabilities, they often rely heavily on human input and…

Cryptography and Security · Computer Science 2025-03-21 Andy Zhou , Kevin Wu , Francesco Pinto , Zhaorun Chen , Yi Zeng , Yu Yang , Shuang Yang , Sanmi Koyejo , James Zou , Bo Li

Automated red-teaming has emerged as a scalable approach for auditing Large Language Models (LLMs) prior to deployment, yet existing approaches lack mechanisms to efficiently adapt to model-specific vulnerabilities at inference. We…

Computation and Language · Computer Science 2026-05-19 Christos Ziakas , Nicholas Loo , Nishita Jain , Alessandra Russo

Customizing pre-trained text-to-image generation model has attracted massive research interest recently, due to its huge potential in real-world applications. Although existing methods are able to generate creative content for a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yufan Zhou , Ruiyi Zhang , Jiuxiang Gu , Tong Sun

AI safety is a rapidly growing area of research that seeks to prevent the harm and misuse of frontier AI technology, particularly with respect to generative AI (GenAI) tools that are capable of creating realistic and high-quality content…

Artificial Intelligence · Computer Science 2025-02-19 Pin-Yu Chen

Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of applications, e.g., medical question-answering, mathematical sciences, and code generation. However, they also exhibit inherent limitations, such…

Cryptography and Security · Computer Science 2025-06-23 Yang Jiao , Xiaodong Wang , Kai Yang

Recent advances in diffusion models have notably enhanced text-to-image (T2I) generation quality, but they also raise the risk of generating unsafe content. Traditional safety methods like text blacklisting or harmful content classification…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zongsheng Cao , Yangfan He , Anran Liu , Jun Xie , Feng Chen , Zepeng Wang

Human motion generation driven by deep generative models has enabled compelling applications, but the ability of text-to-motion (T2M) models to produce realistic motions from text prompts raises security concerns if exploited maliciously.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Honglei Miao , Fan Ma , Ruijie Quan , Kun Zhan , Yi Yang

Text-to-Image (TTI) models are powerful creative tools but risk amplifying harmful social biases. We frame representational societal bias assessment as an image curation and evaluation task and introduce a pilot benchmark of occupational…

Computation and Language · Computer Science 2025-09-03 Shaina Raza , Maximus Powers , Partha Pratim Saha , Mahveen Raza , Rizwan Qureshi

Text-to-image generative models have recently exploded in popularity and accessibility. Yet so far, use of these models in creative tasks that bridge the 2D digital world and the creation of physical artefacts has been understudied. We…

Artificial Intelligence · Computer Science 2023-02-02 Amy Smith , Hope Schroeder , Ziv Epstein , Michael Cook , Simon Colton , Andrew Lippman

Vision-Language-Action (VLA) models have achieved remarkable success in robotic manipulation. However, their robustness to linguistic nuances remains a critical, under-explored safety concern, posing a significant safety risk to real-world…

Robotics · Computer Science 2026-04-08 Baoshun Tong , Haoran He , Ling Pan , Yang Liu , Liang Lin

As generative AI technologies find more and more real-world applications, the importance of testing their performance and safety seems paramount. "Red-teaming" has quickly become the primary approach to test AI models--prioritized by AI…

Computers and Society · Computer Science 2026-01-09 Tarleton Gillespie , Ryland Shaw , Mary L. Gray , Jina Suh

As Large Language Models (LLMs) are deployed and integrated into thousands of applications, the need for scalable evaluation of how models respond to adversarial attacks grows rapidly. However, LLM security is a moving target: models…

Computation and Language · Computer Science 2024-06-18 Leon Derczynski , Erick Galinkin , Jeffrey Martin , Subho Majumdar , Nanna Inie

Text-to-image models such as stable diffusion have opened a plethora of opportunities for generating art. Recent literature has surveyed the use of text-to-image models for enhancing the work of many creative artists. Many e-commerce…

Human-Computer Interaction · Computer Science 2024-03-12 Shanu Vashishtha , Abhinav Prakash , Lalitesh Morishetti , Kaushiki Nag , Yokila Arora , Sushant Kumar , Kannan Achan

The tremendous recent advances in generative artificial intelligence techniques have led to significant successes and promise in a wide range of different applications ranging from conversational agents and textual content generation to…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Hossein Aboutalebi , Dayou Mao , Rongqi Fan , Carol Xu , Chris He , Alexander Wong
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