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Despite the impressive advances in text-to-image models, they often struggle to effectively compose complex scenes with multiple objects, displaying various attributes and relationships. To address this challenge, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Kaiyi Huang , Chengqi Duan , Kaiyue Sun , Enze Xie , Zhenguo Li , Xihui Liu

Large Language Models (LLMs) have demonstrated exceptional performance across various tasks, but their security vulnerabilities can be exploited by attackers to generate harmful content, causing adverse impacts across various societal…

Cryptography and Security · Computer Science 2025-12-17 Fan Yang

Large Language Models face security threats from jailbreak attacks. Existing research has predominantly focused on prompt-level attacks while largely ignoring the underexplored attack surface of user-controlled response prefilling. This…

Cryptography and Security · Computer Science 2025-08-27 Yakai Li , Jiekang Hu , Weiduan Sang , Luping Ma , Dongsheng Nie , Weijuan Zhang , Aimin Yu , Yi Su , Qingjia Huang , Qihang Zhou

As text-to-image (T2I) models advance and gain widespread adoption, their associated safety concerns are becoming increasingly critical. Malicious users exploit these models to generate Not-Safe-for-Work (NSFW) images using harmful or…

Cryptography and Security · Computer Science 2025-12-10 Yiming Wang , Jiahao Chen , Qingming Li , Tong Zhang , Rui Zeng , Xing Yang , Shouling Ji

While recent text-to-image (T2I) models show impressive capabilities in synthesizing images from brief descriptions, their performance significantly degrades when confronted with long, detail-intensive prompts required in professional…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Qirui Jiao , Daoyuan Chen , Yilun Huang , Xika Lin , Ying Shen , Yaliang Li

Current image generation models produce visually compelling but scientifically implausible images, exposing a fundamental gap between visual fidelity and physical realism. In this work, we introduce ScienceT2I, an expert-annotated dataset…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Jialuo Li , Wenhao Chai , Xingyu Fu , Haiyang Xu , Saining Xie

Optimization-based jailbreaks typically adopt the Toxic-Continuation setting in large vision-language models (LVLMs), following the standard next-token prediction objective. In this setting, an adversarial image is optimized to make the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Hee-Seon Kim , Minbeom Kim , Wonjun Lee , Kihyun Kim , Changick Kim

Text-to-image (T2I) models are capable of generating visually impressive images, yet they often fail to accurately capture specific attributes in user prompts, such as the correct number of objects with the specified colors. The diversity…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Kevin David Hayes , Micah Goldblum , Vikash Sehwag , Gowthami Somepalli , Ashwinee Panda , Tom Goldstein

Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting to be integrated into higher-impact pipelines. Since generated images tend to reinforce…

Computers and Society · Computer Science 2026-05-14 Jose Luna , Yankun Wu , Xiaofei Xie , Noa Garcia

Text-to-image generation models have recently attracted unprecedented attention as they unlatch imaginative applications in all areas of life. However, developing such models requires huge amounts of data that might contain…

Cryptography and Security · Computer Science 2022-10-04 Yixin Wu , Ning Yu , Zheng Li , Michael Backes , Yang Zhang

With the increasing use of image generation technology, understanding its social biases, including gender bias, is essential. This paper presents a large-scale study on gender bias in text-to-image (T2I) models, focusing on everyday…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Leander Girrbach , Stephan Alaniz , Genevieve Smith , Zeynep Akata

Text-to-Image (T2I) generative models have revolutionized content creation, yet they inherently risk amplifying societal biases. While sociological research provides systematic classifications of bias, existing T2I benchmarks largely…

Computers and Society · Computer Science 2026-04-15 Hanjun Luo , Zhimu Huang , Haoyu Huang , Ziye Deng , Ruizhe Chen , Xinfeng Li , Zuozhu Liu , Hanan Salam

Text-to-image (T2I) models have advanced creative content generation, yet their reliance on large uncurated datasets often reproduces societal biases. We present FairT2I, a training-free and interactive framework grounded in a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Jinya Sakurai , Yuki Koyama , Issei Sato

The recent advancement of large and powerful models with Text-to-Image (T2I) generation abilities -- such as OpenAI's DALLE-3 and Google's Gemini -- enables users to generate high-quality images from textual prompts. However, it has become…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yixin Wan , Arjun Subramonian , Anaelia Ovalle , Zongyu Lin , Ashima Suvarna , Christina Chance , Hritik Bansal , Rebecca Pattichis , Kai-Wei Chang

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

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Manuel Brack , Patrick Schramowski , Kristian Kersting

Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models still struggle with prompts that require rich world knowledge and implicit reasoning: both of which are critical for producing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Daoan Zhang , Che Jiang , Ruoshi Xu , Biaoxiang Chen , Zijian Jin , Yutian Lu , Jianguo Zhang , Liang Yong , Jiebo Luo , Shengda Luo

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

Text-to-image (T2I) models have garnered significant attention for generating high-quality images aligned with text prompts. However, rapid T2I model advancements reveal limitations in early benchmarks, lacking comprehensive evaluations,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Jingjing Chang , Yixiao Fang , Peng Xing , Shuhan Wu , Wei Cheng , Rui Wang , Xianfang Zeng , Gang Yu , Hai-Bao Chen

Despite the remarkable synthesis capabilities of text-to-image (T2I) models, safeguarding them against content violations remains a persistent challenge. Existing safety alignments primarily focus on explicit malicious concepts, often…

Cryptography and Security · Computer Science 2026-04-20 Chaoshuo Zhang , Yibo Liang , Mengke Tian , Chenhao Lin , Zhengyu Zhao , Le Yang , Chong Zhang , Yang Zhang , Chao Shen

The rapid advancement of generative AI highlights the importance of text-to-image (T2I) security, particularly with the threat of backdoor poisoning. Timely disclosure and mitigation of security vulnerabilities in T2I models are crucial for…

Cryptography and Security · Computer Science 2025-04-22 Chongye Guo , Jinhu Fu , Junfeng Fang , Kun Wang , Guorui Feng
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