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Related papers: Chaining text-to-image and large language model: A…

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This paper does not describe a new method; instead, it provides a thorough exploration of an important yet understudied design space related to recent advances in text-to-image synthesis -- specifically, the deep fusion of large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Bingda Tang , Boyang Zheng , Xichen Pan , Sayak Paul , Saining Xie

Recent advances in text-to-image generation models have unlocked vast potential for visual creativity. However, the users that use these models struggle with the generation of consistent characters, a crucial aspect for numerous real-world…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Omri Avrahami , Amir Hertz , Yael Vinker , Moab Arar , Shlomi Fruchter , Ohad Fried , Daniel Cohen-Or , Dani Lischinski

Automatic generation of graphical layouts is crucial for many real-world applications, including designing posters, flyers, advertisements, and graphical user interfaces. Given the incredible ability of Large language models (LLMs) in both…

Computation and Language · Computer Science 2024-10-18 Jian Chen , Ruiyi Zhang , Yufan Zhou , Jennifer Healey , Jiuxiang Gu , Zhiqiang Xu , Changyou Chen

The rapid progress of text-to-image diffusion models raises significant concerns regarding the unauthorized reproduction of trademarked content. While prior work targets general concepts (e.g., styles, celebrities), it fails to address…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Dawid Malarz , Filip Manjak , Maciej Zięba , Przemysław Spurek , Artur Kasymov

Text-to-image generation has recently seen remarkable success, granting users with the ability to create high-quality images through the use of text. However, contemporary methods face challenges in capturing the precise semantics conveyed…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Shay Shomer-Chai , Wenxuan Peng , Bharath Hariharan , Hadar Averbuch-Elor

Text-to-image diffusion models have recently taken center stage as pivotal tools in promoting visual creativity across an array of domains such as comic book artistry, children's literature, game development, and web design. These models…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Kiymet Akdemir , Pinar Yanardag

With the advancement of large language models (LLMs), the focus in Conversational AI has shifted from merely generating coherent and relevant responses to tackling more complex challenges, such as personalizing dialogue systems. In an…

Computation and Language · Computer Science 2025-02-13 Maria Molchanova , Anna Mikhailova , Anna Korzanova , Lidiia Ostyakova , Alexandra Dolidze

Despite recent progress in text-to-image (T2I) generation, existing models often struggle to faithfully capture user intentions from short and under-specified prompts. While prior work has attempted to enhance prompts using large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Mingrui Wu , Lu Wang , Pu Zhao , Fangkai Yang , Jianjin Zhang , Jianfeng Liu , Yuefeng Zhan , Weihao Han , Hao Sun , Jiayi Ji , Xiaoshuai Sun , Qingwei Lin , Weiwei Deng , Dongmei Zhang , Feng Sun , Qi Zhang , Rongrong Ji

Text-to-image diffusion models have demonstrated tremendous success in synthesizing visually stunning images given textual instructions. Despite remarkable progress in creating high-fidelity visuals, text-to-image models can still struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Taewook Kim , Ze Wang , Zhengyuan Yang , Jiang Wang , Lijuan Wang , Zicheng Liu , Qiang Qiu

Large language models (LLMs) have made tremendous progress in natural language understanding and they have also been successfully adopted in other domains such as computer vision, robotics, reinforcement learning, etc. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Reza Pourreza , Apratim Bhattacharyya , Sunny Panchal , Mingu Lee , Pulkit Madan , Roland Memisevic

Text-to-image generative models, specifically those based on diffusion models like Imagen and Stable Diffusion, have made substantial advancements. Recently, there has been a surge of interest in the delicate refinement of text prompts.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Wenyi Mo , Tianyu Zhang , Yalong Bai , Bing Su , Ji-Rong Wen , Qing Yang

We introduce a simple approach that uses a large language model (LLM) to automatically implement a fully interpretable rule-based data-to-text system in pure Python. Experimental evaluation on the WebNLG dataset showed that such a…

Computation and Language · Computer Science 2025-03-03 Jędrzej Warczyński , Mateusz Lango , Ondrej Dusek

Text-to-image generative models can produce diverse high-quality images of concepts with a text prompt, which have demonstrated excellent ability in image generation, image translation, etc. We in this work study the problem of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-11 Gan Sun , Wenqi Liang , Jiahua Dong , Jun Li , Zhengming Ding , Yang Cong

Deep generative models have shown impressive results in text-to-image synthesis. However, current text-to-image models often generate images that are inadequately aligned with text prompts. We propose a fine-tuning method for aligning such…

Text-to-image person re-identification (ReID) retrieves pedestrian images according to textual descriptions. Manually annotating textual descriptions is time-consuming, restricting the scale of existing datasets and therefore the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Wentao Tan , Changxing Ding , Jiayu Jiang , Fei Wang , Yibing Zhan , Dapeng Tao

With the large language model showing human-like logical reasoning and understanding ability, whether agents based on the large language model can simulate the interaction behavior of real users, so as to build a reliable virtual…

Information Retrieval · Computer Science 2024-03-05 Chenwei Zhang , Wenran Lu , Chunhe Ni , Hongbo Wang , Jiang Wu

Recent advancements in diffusion models have introduced fast sampling methods that can effectively produce high-quality images in just one or a few denoising steps. Interestingly, when these are distilled from existing diffusion models,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Rinon Gal , Or Lichter , Elad Richardson , Or Patashnik , Amit H. Bermano , Gal Chechik , Daniel Cohen-Or

Customized generative text-to-image models have the ability to produce images that closely resemble a given subject. However, in the context of generating advertising images for e-commerce scenarios, it is crucial that the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Youze Xue , Binghui Chen , Yifeng Geng , Xuansong Xie , Jiansheng Chen , Hongbing Ma

While generative models produce high-quality images of concepts learned from a large-scale database, a user often wishes to synthesize instantiations of their own concepts (for example, their family, pets, or items). Can we teach a model to…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Nupur Kumari , Bingliang Zhang , Richard Zhang , Eli Shechtman , Jun-Yan Zhu

Text-to-image (T2I) models such as Stable Diffusion have advanced rapidly and are now widely used in content creation. However, these models can be misused to generate harmful content, including nudity or violence, posing significant safety…

Cryptography and Security · Computer Science 2025-06-13 Zilong Wang , Xiang Zheng , Xiaosen Wang , Bo Wang , Xingjun Ma , Yu-Gang Jiang