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Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with generative AI. However, such models often fail to connect the generated outputs and desired target…

Machine Learning · Computer Science 2026-04-15 Melvin Wong , Yew-Soon Ong , Abhishek Gupta , Kavitesh K. Bali , Caishun Chen

Recent progress in generative models, especially in text-guided diffusion models, has enabled the production of aesthetically-pleasing imagery resembling the works of professional human artists. However, one has to carefully compose the…

Human-Computer Interaction · Computer Science 2023-06-05 Nikita Pavlichenko , Dmitry Ustalov

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

Large Language Models (LLMs) have gained widespread popularity due to their ability to perform ad-hoc Natural Language Processing (NLP) tasks with a simple natural language prompt. Part of the appeal for LLMs is their approachability to the…

Human-Computer Interaction · Computer Science 2025-02-25 Aditi Mishra , Utkarsh Soni , Anjana Arunkumar , Jinbin Huang , Bum Chul Kwon , Chris Bryan

Customizing pre-trained text-to-image generation model has attracted massive research interest recently, due to its huge potential in real-world applications. Although existing methods are able to generate creative content for a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yufan Zhou , Ruiyi Zhang , Jiuxiang Gu , Tong Sun

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

Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text prompts. Such text-based synthesis methods are particularly…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Amir Hertz , Ron Mokady , Jay Tenenbaum , Kfir Aberman , Yael Pritch , Daniel Cohen-Or

Crafting a rich and unique environment is crucial for fictional world-building, but can be difficult to achieve since illustrating a world from scratch requires time and significant skill. We investigate the use of recent multi-modal image…

Human-Computer Interaction · Computer Science 2023-08-28 Hai Dang , Frederik Brudy , George Fitzmaurice , Fraser Anderson

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

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

Creative generation is the synthesis of new, surprising, and valuable samples that reflect user intent yet cannot be envisioned in advance. This task aims to extend human imagination, enabling the discovery of visual concepts that exist in…

Graphics · Computer Science 2025-10-14 Shelly Golan , Yotam Nitzan , Zongze Wu , Or Patashnik

Text-to-image models have made significant strides, producing impressive results in generating images from textual descriptions. However, creating a scalable pipeline for deploying these models in production remains a challenge. Achieving…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Parmida Atighehchian , Henry Wang , Andrei Kapustin , Boris Lerner , Tiancheng Jiang , Taylor Jensen , Negin Sokhandan

Text-to-Image models, including Stable Diffusion, have significantly improved in generating images that are highly semantically aligned with the given prompts. However, existing models may fail to produce appropriate images for the cultural…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Suchae Jeong , Inseong Choi , Youngsik Yun , Jihie Kim

Facial images have extensive practical applications. Although the current large-scale text-image diffusion models exhibit strong generation capabilities, it is challenging to generate the desired facial images using only text prompt. Image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Dawei Dai , Mingming Jia , Yinxiu Zhou , Hang Xing , Chenghang Li

The emergence of generative AI (GenAI) models, including large language models and text-to-image models, has significantly advanced the synergy between humans and AI with not only their outstanding capability but more importantly, the…

Human-Computer Interaction · Computer Science 2025-03-05 Leixian Shen , Haotian Li , Yifang Wang , Xing Xie , Huamin Qu

Prompt engineering is still the primary way for users of generative text-to-image models to manipulate generated images in a targeted way. Based on treating the model as a continuous function and by passing gradients between the image space…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Niklas Deckers , Julia Peters , Martin Potthast

Traditional ML models utilize controlled approximations during high loads, employing faster, but less accurate models in a process called accuracy scaling. However, this method is less effective for generative text-to-image models due to…

Machine Learning · Computer Science 2025-02-12 Shubham Agarwal , Saud Iqbal , Subrata Mitra

Conditional generative models such as DALL-E and Stable Diffusion generate images based on a user-defined text, the prompt. Finding and refining prompts that produce a desired image has become the art of prompt engineering. Generative…

Information Retrieval · Computer Science 2023-01-24 Niklas Deckers , Maik Fröbe , Johannes Kiesel , Gianluca Pandolfo , Christopher Schröder , Benno Stein , Martin Potthast

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

Prompt engineering is crucial for achieving reliable and effective outputs from large language models (LLMs), but its design requires specialized knowledge of prompting techniques and a deep understanding of target tasks. To address this…

Computation and Language · Computer Science 2025-10-22 Yohei Ikenoue , Hitomi Tashiro , Shigeru Kuroyanagi