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Feedback is crucial for every design process, such as user interface (UI) design, and automating design critiques can significantly improve the efficiency of the design workflow. Although existing multimodal large language models (LLMs)…

Artificial Intelligence · Computer Science 2025-05-26 Peitong Duan , Chin-Yi Cheng , Bjoern Hartmann , Yang Li

Impressive advances in text-to-image (T2I) generative models have yielded a plethora of high performing models which are able to generate aesthetically appealing, photorealistic images. Despite the progress, these models still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Oscar Mañas , Pietro Astolfi , Melissa Hall , Candace Ross , Jack Urbanek , Adina Williams , Aishwarya Agrawal , Adriana Romero-Soriano , Michal Drozdzal

Recent advances in text-to-image diffusion models have achieved impressive image generation capabilities. However, it remains challenging to control the generation process with desired properties (e.g., aesthetic quality, user intention),…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Taeyoung Yun , Dinghuai Zhang , Jinkyoo Park , Ling Pan

The rapid development of the Internet has profoundly changed human life. Humans are increasingly expressing themselves and interacting with others on social media platforms. However, although artificial intelligence technology has been…

Computation and Language · Computer Science 2024-07-11 Haochen Xue , Chong Zhang , Chengzhi Liu , Fangyu Wu , Xiaobo Jin

The recent trend in the Large Vision and Language model has brought a new change in how information extraction systems are built. VLMs have set a new benchmark with their State-of-the-art techniques in understanding documents and building…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Dipankar Medhi

The emergence of text-to-image synthesis (TIS) models has significantly influenced digital image creation by producing high-quality visuals from written descriptions. Yet these models are sensitive on textual prompts, posing a challenge for…

Artificial Intelligence · Computer Science 2025-10-15 Yilun Liu , Minggui He , Feiyu Yao , Yuhe Ji , Shimin Tao , Jingzhou Du , Duan Li , Jian Gao , Li Zhang , Hao Yang , Boxing Chen , Osamu Yoshie

Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex prompts, such as those that involve numeracy and spatial…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Long Lian , Boyi Li , Adam Yala , Trevor Darrell

Prompting is a mainstream paradigm for adapting large language models to specific natural language processing tasks without modifying internal parameters. Therefore, detailed supplementary knowledge needs to be integrated into external…

Computation and Language · Computer Science 2024-12-03 Kaiyan Chang , Songcheng Xu , Chenglong Wang , Yingfeng Luo , Xiaoqian Liu , Tong Xiao , Jingbo Zhu

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 generation methods (T2I) are widely popular in generating art and other creative artifacts. While visual hallucinations can be a positive factor in scenarios where creativity is appreciated, such artifacts are poorly suited…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Rodrigo Valerio , Joao Bordalo , Michal Yarom , Yonatan Bitton , Idan Szpektor , Joao Magalhaes

Despite substantial progress in text-to-image generation, achieving precise text-image alignment remains challenging, particularly for prompts with rich compositional structure or imaginative elements. To address this, we introduce Negative…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Sangha Park , Eunji Kim , Yeongtak Oh , Jooyoung Choi , Sungroh Yoon

Prompt learning is an effective paradigm that bridges gaps between the pre-training tasks and the corresponding downstream applications. Approaches based on this paradigm have achieved great transcendent results in various applications.…

Information Retrieval · Computer Science 2022-09-26 Zhigang Kan , Linhui Feng , Zhangyue Yin , Linbo Qiao , Xipeng Qiu , Dongsheng Li

Text-to-image generation systems have emerged as revolutionary tools in the realm of artistic creation, offering unprecedented ease in transforming textual prompts into visual art. However, the efficacy of these systems is intricately…

Computation and Language · Computer Science 2024-04-01 Jingtao Zhan , Qingyao Ai , Yiqun Liu , Jia Chen , Shaoping Ma

Text-to-image generation has become increasingly popular, but achieving the desired images often requires extensive prompt engineering. In this paper, we explore how to decode textual prompts from reference images, a process we refer to as…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Zhiyao Ren , Yibing Zhan , Baosheng Yu , Dacheng Tao

Transformer-based Large Language Models (LLMs) have shown exceptional language generation capabilities in response to text-based prompts. However, controlling the direction of generation via textual prompts has been challenging, especially…

Computation and Language · Computer Science 2024-04-09 Rohan Deepak Ajwani , Zining Zhu , Jonathan Rose , Frank Rudzicz

Recommender Systems are built to retrieve relevant items to satisfy users' information needs. The candidate corpus usually consists of a finite set of items that are ready to be served, such as videos, products, or articles. With recent…

Information Retrieval · Computer Science 2023-12-08 Yuanhe Guo , Haoming Liu , Hongyi Wen

Recent virtual try-on approaches have advanced by finetuning pre-trained text-to-image diffusion models to leverage their powerful generative ability. However, the use of text prompts in virtual try-on remains underexplored. This paper…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Jeongho Kim , Hoiyeong Jin , Sunghyun Park , Jaegul Choo

Editing images via instruction provides a natural way to generate interactive content, but it is a big challenge due to the higher requirement of scene understanding and generation. Prior work utilizes a chain of large language models,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Liya Ji , Chenyang Qi , Qifeng Chen

This paper assesses the potential for large language models (LLMs) to serve as assistive tools in the creative writing process, by means of a single, in-depth case study. In the course of the study, we develop interactive and multi-voice…

Computation and Language · Computer Science 2023-12-08 Murray Shanahan , Catherine Clarke

For text-to-image generation, automatically refining user-provided natural language prompts into the keyword-enriched prompts favored by systems is essential for the user experience. Such a prompt refinement process is analogous to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Jingtao Zhan , Qingyao Ai , Yiqun Liu , Yingwei Pan , Ting Yao , Jiaxin Mao , Shaoping Ma , Tao Mei
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