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Generative models are increasingly powerful, yet users struggle to guide them through prompts. The generative process is difficult to control and unpredictable, and user instructions may be ambiguous or under-specified. Prior prompt…

Human-Computer Interaction · Computer Science 2026-02-16 Zhipeng Li , Yi-Chi Liao , Christian Holz

With the advancement of neural generative capabilities, the art community has increasingly embraced GenAI (Generative Artificial Intelligence), particularly large text-to-image models, for producing aesthetically compelling results.…

Human-Computer Interaction · Computer Science 2025-08-26 Aven-Le Zhou , Wei Wu , Yu-Ao Wang , Kang Zhang

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

Generative AI for the creation of images is becoming a staple in the toolkit of digital artists and visual designers. The interaction with these systems is mediated by \emph{prompting}, a process in which users write a short text to…

Computers and Society · Computer Science 2024-02-20 Maddalena Torricelli , Mauro Martino , Andrea Baronchelli , Luca Maria Aiello

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

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

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

With the advancement of neural generative capabilities, the art community has actively embraced GenAI (generative artificial intelligence) for creating painterly content. Large text-to-image models can quickly generate aesthetically…

Artificial Intelligence · Computer Science 2024-02-12 Aven-Le Zhou , Yu-Ao Wang , Wei Wu , Kang Zhang

It has been shown that many generative models inherit and amplify societal biases. To date, there is no uniform/systematic agreed standard to control/adjust for these biases. This study examines the presence and manipulation of societal…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Philip Wootaek Shin , Jihyun Janice Ahn , Wenpeng Yin , Jack Sampson , Vijaykrishnan Narayanan

Text-to-image models are enabling efficient design space exploration, rapidly generating images from text prompts. However, many generative AI tools are imperfect for product design applications as they are not built for the goals and…

Human-Computer Interaction · Computer Science 2025-01-22 Leah Chong , I-Ping Lo , Jude Rayan , Steven Dow , Faez Ahmed , Ioanna Lykourentzou

Deep generative models have the potential to fundamentally change the way we create high-fidelity digital content but are often hard to control. Prompting a generative model is a promising recent development that in principle enables…

Human-Computer Interaction · Computer Science 2022-09-07 Hai Dang , Lukas Mecke , Florian Lehmann , Sven Goller , Daniel Buschek

Text-to-image generation has progressed rapidly, but faithfully generating complex scenes requires extensive trial-and-error to find the exact prompt. In the prompt inversion task, the goal is to recover a textual prompt that can faithfully…

Machine Learning · Computer Science 2026-04-30 Asaf Buchnick , Aviv Shamsian , Aviv Navon , Ethan Fetaya

Different users find different images generated for the same prompt desirable. This gives rise to personalized image generation which involves creating images aligned with an individual's visual preference. Current generative models are,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Sogand Salehi , Mahdi Shafiei , Teresa Yeo , Roman Bachmann , Amir Zamir

The performance of computer vision models in certain real-world applications (e.g., rare wildlife observation) is limited by the small number of available images. Expanding datasets using pre-trained generative models is an effective way to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Changjian Chen , Fei Lv , Yalong Guan , Pengcheng Wang , Shengjie Yu , Yifan Zhang , Zhuo Tang

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

This paper argues that generative art driven by conformance to a visual and/or semantic corpus lacks the necessary criteria to be considered creative. Among several issues identified in the literature, we focus on the fact that generative…

Artificial Intelligence · Computer Science 2022-05-03 Marvin Zammit , Antonios Liapis , Georgios N. Yannakakis

Preference-conditioned image generation seeks to adapt generative models to individual users, producing outputs that reflect personal aesthetic choices beyond the given textual prompt. Despite recent progress, existing approaches either…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Wenyi Mo , Tianyu Zhang , Yalong Bai , Ligong Han , Ying Ba , Dimitris N. Metaxas

Despite the rapid evolution and increasing efficacy of language and vision generative models, there remains a lack of comprehensive datasets that bridge the gap between personalized fashion needs and AI-driven design, limiting the potential…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Georgia Argyrou , Angeliki Dimitriou , Maria Lymperaiou , Giorgos Filandrianos , Giorgos Stamou

Text-to-image generation has seen an explosion of interest since 2021. Today, beautiful and intriguing digital images and artworks can be synthesized from textual inputs ("prompts") with deep generative models. Online communities around…

Multimedia · Computer Science 2023-11-27 Jonas Oppenlaender

Creativity is a valuable human skill that has long been augmented through both analog and digital tools. Recent progress in generative AI, such as image generation, provides a disruptive technological solution to supporting human creativity…

Human-Computer Interaction · Computer Science 2025-06-05 Daniel Hove Paludan , Julie Fredsgård , Kasper Patrick Bährentz , Ilhan Aslan , Niels van Berkel
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