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Despite significant progress in the field, it is still challenging to create personalized visual representations that align closely with the desires and preferences of individual users. This process requires users to articulate their ideas…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Zijie Chen , Lichao Zhang , Fangsheng Weng , Lili Pan , Zhenzhong Lan

Text-to-3D generative AI systems create navigable environments from natural language prompts, but unlike text-to-image generation, evaluation requires embodied exploration of spatial coherence, scale, and navigability. We present the first…

Human-Computer Interaction · Computer Science 2026-03-17 Aung Pyae

Generative AI models have shown impressive ability to produce images with text prompts, which could benefit creativity in visual art creation and self-expression. However, it is unclear how precisely the generated images express contexts…

Human-Computer Interaction · Computer Science 2023-03-21 Yunlong Wang , Shuyuan Shen , Brian Y. Lim

UI task automation enables efficient task execution by simulating human interactions with graphical user interfaces (GUIs), without modifying the existing application code. However, its broader adoption is constrained by the need for…

Human-Computer Interaction · Computer Science 2025-03-19 Tian Huang , Chun Yu , Weinan Shi , Zijian Peng , David Yang , Weiqi Sun , Yuanchun Shi

Generative AI (GenAI) image tools are increasingly used in design practice, enabling rapid ideation but offering limited support for refinement tasks such as adjusting layout, scale, or visual attributes. While text prompts and inpainting…

Human-Computer Interaction · Computer Science 2026-02-10 Hyerim Park , Phuong Thao Tran , Andre Luckow , Ceenu George , Michael Sedlmair , Malin Eiband

Generative AI models are increasingly being integrated into human task workflows, enabling the production of expressive content across a wide range of contexts. Unlike traditional human-AI design methods, the new approach to designing…

Human-Computer Interaction · Computer Science 2025-04-01 Hari Subramonyam , Divy Thakkar , Andrew Ku , Jürgen Dieber , Anoop Sinha

Complex data analysis inherently seeks unexpected insights through exploratory visual analysis methods, transcending logical, step-by-step processing. However, existing interfaces such as notebooks and dashboards have limitations in…

Human-Computer Interaction · Computer Science 2024-03-22 Zijian Ding , Joel Chan

Well-designed prompts can guide text-to-image models to generate amazing images. However, the performant prompts are often model-specific and misaligned with user input. Instead of laborious human engineering, we propose prompt adaptation,…

Computation and Language · Computer Science 2024-01-01 Yaru Hao , Zewen Chi , Li Dong , Furu Wei

Image generation using generative artificial intelligence has become a popular activity. However, text-to-image generation - where images are produced from typed prompts - can be less engaging in public settings since the act of typing…

Human-Computer Interaction · Computer Science 2025-02-18 Jonas Oppenlaender , Hannah Johnston , Johanna Silvennoinen , Helena Barranha

We present WorldCanvas, a framework for promptable world events that enables rich, user-directed simulation by combining text, trajectories, and reference images. Unlike text-only approaches and existing trajectory-controlled image-to-video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Hanlin Wang , Hao Ouyang , Qiuyu Wang , Yue Yu , Yihao Meng , Wen Wang , Ka Leong Cheng , Shuailei Ma , Qingyan Bai , Yixuan Li , Cheng Chen , Yanhong Zeng , Xing Zhu , Yujun Shen , Qifeng Chen

Text-to-image generation models are powerful but difficult to use. Users craft specific prompts to get better images, though the images can be repetitive. This paper proposes a Prompt Expansion framework that helps users generate…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Siddhartha Datta , Alexander Ku , Deepak Ramachandran , Peter Anderson

Traditional visualisation designers often start with sketches before implementation. With generative AI, these sketches can be turned into AI-generated visualisations using specific prompts. However, guiding AI to create compelling visuals…

Human-Computer Interaction · Computer Science 2024-09-04 Aron E. Owen , Jonathan C. Roberts

This paper examines the art practices, artwork, and motivations of prolific users of the latest generation of text-to-image models. Through interviews, observations, and a user survey, we present a sampling of the artistic styles and…

Human-Computer Interaction · Computer Science 2023-03-23 Minsuk Chang , Stefania Druga , Alex Fiannaca , Pedro Vergani , Chinmay Kulkarni , Carrie Cai , Michael Terry

We present an account of an ongoing practice-based Design Research programme that explores the interaction affordances of real-time AI image generators. Based on our experiences from three installations, we reflect on the design of PromptJ,…

Human-Computer Interaction · Computer Science 2025-04-10 Joseph Lindley , Roger Whitham

Generative AI has enabled novice designers to quickly create professional-looking visual representations for product concepts. However, novices have limited domain knowledge that could constrain their ability to write prompts that…

Human-Computer Interaction · Computer Science 2026-03-30 Sirui Tao , Ivan Liang , Cindy Peng , Zhiqing Wang , Srishti Palani , Steven P. Dow

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

Generative text-to-image models, which allow users to create appealing images through a text prompt, have seen a dramatic increase in popularity in recent years. However, most users have a limited understanding of how such models work and…

Human-Computer Interaction · Computer Science 2024-03-15 Yuhan Guo , Hanning Shao , Can Liu , Kai Xu , Xiaoru Yuan

Text-to-image generative models can be tremendously valuable in supporting creative tasks by providing inspirations and enabling quick exploration of different design ideas. However, one common challenge is that users may still not be able…

Human-Computer Interaction · Computer Science 2025-10-06 Yuhan Guo , Xingyou Liu , Xiaoru Yuan , Kai Xu

Natural language remains the predominant way people interact with large language models (LLMs). However, users often struggle to precisely express and control subjective preferences (e.g., tone, style, and emphasis) through prompting. We…

Human-Computer Interaction · Computer Science 2026-04-14 Chao Zhang , Yiren Liu , Lunyiu Nie , Jeffrey M. Rzeszotarski , Yun Huang , Tal August

Recently, diffusion-based deep generative models (e.g., Stable Diffusion) have shown impressive results in text-to-image synthesis. However, current text-to-image models often require multiple passes of prompt engineering by humans in order…

Computation and Language · Computer Science 2023-11-14 Tingfeng Cao , Chengyu Wang , Bingyan Liu , Ziheng Wu , Jinhui Zhu , Jun Huang