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Related papers: IA-T2I: Internet-Augmented Text-to-Image Generatio…

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With advances in the quality of text-to-image (T2I) models has come interest in benchmarking their prompt faithfulness -- the semantic coherence of generated images to the prompts they were conditioned on. A variety of T2I faithfulness…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Michael Saxon , Fatima Jahara , Mahsa Khoshnoodi , Yujie Lu , Aditya Sharma , William Yang Wang

Text-to-image (T2I) generative models are largely used in AI-powered real-world applications and value creation. However, their strategic deployment raises critical concerns for responsible AI management, particularly regarding the…

Machine Learning · Computer Science 2025-11-18 Abu Sufian , Cosimo Distante , Marco Leo , Hanan Salam

Video generation models are revolutionizing content creation, with image-to-video models drawing increasing attention due to their enhanced controllability, visual consistency, and practical applications. However, despite their popularity,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Wenhao Wang , Yi Yang

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. However, the effective integration of T2I models into…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhicai Wang , Longhui Wei , Tan Wang , Heyu Chen , Yanbin Hao , Xiang Wang , Xiangnan He , Qi Tian

While modern text-to-image (T2I) models excel at generating images from intricate prompts, they struggle to capture the key details when the inputs are descriptive paragraphs. This limitation stems from the prevalence of concise captions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Jen-Yuan Huang , Tong Lin , Yilun Du

Text-to-image (T2I) generative models achieve impressive visual fidelity but inherit and amplify demographic imbalances and cultural biases embedded in training data. We introduce T2I-BiasBench, a unified evaluation framework of thirteen…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Nihal Jaiswal , Siddhartha Arjaria , Gyanendra Chaubey , Ankush Kumar , Aditya Singh , Anchal Chaurasiya

As large language models have demonstrated impressive performance in many domains, recent works have adopted language models (LMs) as controllers of visual modules for vision-and-language tasks. While existing work focuses on equipping LMs…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Jaemin Cho , Abhay Zala , Mohit Bansal

Although text-to-image generation technologies have made significant advancements, they still face challenges when dealing with ambiguous prompts and aligning outputs with user intent.Our proposed framework, TDRI (Two-Phase Dialogue…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yuheng Feng , Jianhui Wang , Kun Li , Sida Li , Tianyu Shi , Haoyue Han , Miao Zhang , Xueqian Wang

Modern text-to-image (T2I) models generate high-fidelity visuals but remain indifferent to individual user preferences. While existing reward models optimize for "average" human appeal, they fail to capture the inherent subjectivity of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Anne-Sofie Maerten , Juliane Verwiebe , Shyamgopal Karthik , Ameya Prabhu , Johan Wagemans , Matthias Bethge

Reasoning is a fundamental capability often required in real-world text-to-image (T2I) generation, e.g., generating ``a bitten apple that has been left in the air for more than a week`` necessitates understanding temporal decay and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Kaijie Chen , Zihao Lin , Zhiyang Xu , Ying Shen , Yuguang Yao , Joy Rimchala , Jiaxin Zhang , Lifu Huang

Recently, creative generative artificial intelligence software has emerged as a pivotal assistant, enabling users to generate content and seek inspiration rapidly. Text-to-Image (T2I) software, one of the most widely used, synthesizes…

Software Engineering · Computer Science 2025-01-14 Siqi Gu , Chunrong Fang , Quanjun Zhang , Zhenyu Chen

Text-to-image generative models have demonstrated remarkable capabilities in generating high-quality images based on textual prompts. However, crafting prompts that accurately capture the user's creative intent remains challenging. It often…

Human-Computer Interaction · Computer Science 2023-04-20 Stephen Brade , Bryan Wang , Mauricio Sousa , Sageev Oore , Tovi Grossman

Text-to-image (T2I) models have become prevalent across numerous applications, making their robust evaluation against adversarial attacks a critical priority. Continuous access to new and challenging adversarial prompts across diverse…

Machine Learning · Computer Science 2025-07-25 Jessica Quaye , Charvi Rastogi , Alicia Parrish , Oana Inel , Minsuk Kahng , Lora Aroyo , Vijay Janapa Reddi

Multilingual text-to-image (T2I) models have advanced rapidly in terms of visual realism and semantic alignment, and are now widely utilized. Yet outputs vary across cultural contexts: because language carries cultural connotations, images…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Chuancheng Shi , Shangze Li , Shiming Guo , Simiao Xie , Wenhua Wu , Jingtong Dou , Chao Wu , Canran Xiao , Cong Wang , Zifeng Cheng , Fei Shen , Tat-Seng Chua

We address the task of advertisement image generation and introduce three evaluation metrics to assess Creativity, prompt Alignment, and Persuasiveness (CAP) in generated advertisement images. Despite recent advancements in Text-to-Image…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Aysan Aghazadeh , Adriana Kovashka

Text-to-image models have shown remarkable progress in generating high-quality images from user-provided prompts. Despite this, the quality of these images varies due to the models' sensitivity to human language nuances. With advancements…

Artificial Intelligence · Computer Science 2024-06-14 Xinrui Yang , Zhuohan Wang , Anthony Hu

We present Infinite-Story, a training-free framework for consistent text-to-image (T2I) generation tailored for multi-prompt storytelling scenarios. Built upon a scale-wise autoregressive model, our method addresses two key challenges in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Jihun Park , Kyoungmin Lee , Jongmin Gim , Hyeonseo Jo , Minseok Oh , Wonhyeok Choi , Kyumin Hwang , Jaeyeul Kim , Minwoo Choi , Sunghoon Im

Despite the rapid progress of text-to-image (T2I) models, generating images that accurately reflect complex compositional prompts (covering attribute bindings, object relationships, counting) still remains challenging. To address this, we…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Zhuohan Liu , Wujian Peng , Yitong Chen , Zuxuan Wu

Diffusion models excel in many generative modeling tasks, notably in creating images from text prompts, a task referred to as text-to-image (T2I) generation. Despite the ability to generate high-quality images, these models often replicate…

Multimedia · Computer Science 2024-02-20 Yang Zhang , Teoh Tze Tzun , Lim Wei Hern , Haonan Wang , Kenji Kawaguchi

We study idiom-based visual puns--images that align an idiom's literal and figurative meanings--and present an iterative framework that coordinates a large language model (LLM), a text-to-image model (T2IM), and a multimodal LLM (MLLM) for…

Computation and Language · Computer Science 2025-12-01 Kelaiti Xiao , Liang Yang , Dongyu Zhang , Paerhati Tulajiang , Hongfei Lin