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The recent advancements in Generative AI have significantly advanced the field of text-to-image generation. The state-of-the-art text-to-image model, Stable Diffusion, is now capable of synthesizing high-quality images with a strong sense…

Human-Computer Interaction · Computer Science 2024-03-08 Zhijie Wang , Yuheng Huang , Da Song , Lei Ma , Tianyi Zhang

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

The rapid progress of large language models (LLMs) has sparked growing interest in building Artificial General Intelligence (AGI) within Graphical User Interface (GUI) environments. However, existing GUI agents based on LLMs or…

Artificial Intelligence · Computer Science 2025-05-27 Runliang Niu , Jinglong Ji , Yi Chang , Qi Wang

Text-to-image (T2I) models, while offering immense creative potential, are highly reliant on human intervention, posing significant usability challenges that often necessitate manual, iterative prompt engineering over often underspecified…

Artificial Intelligence · Computer Science 2025-09-16 Xingchen Wan , Han Zhou , Ruoxi Sun , Hootan Nakhost , Ke Jiang , Rajarishi Sinha , Sercan Ö. Arık

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

Diffusion models excel in many generative modeling tasks, notably in creating images from text prompts, a task referred to as text-to-image (T2I) generation. Despite the ability to generate high-quality images, these models often replicate…

Multimedia · Computer Science 2024-02-20 Yang Zhang , Teoh Tze Tzun , Lim Wei Hern , Haonan Wang , Kenji Kawaguchi

The increasing popularity of long Text-to-Image (T2I) generation has created an urgent need for automatic and interpretable models that can evaluate the image-text alignment in long prompt scenarios. However, the existing T2I alignment…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Zhichao Yang , Tianjiao Gu , Jianjie Wang , Feiyu Lin , Xiangfei Sheng , Pengfei Chen , Leida Li

Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. Recent research has extended these models to support text-guided image editing. While text guidance is an intuitive editing…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Jooyoung Choi , Yunjey Choi , Yunji Kim , Junho Kim , Sungroh Yoon

Recent advances in Machine-Learning have led to the development of models that generate images based on a text description.Such large prompt-based text to image models (TTIs), trained on a considerable amount of data, allow the creation of…

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

Recent advances in diffusion-based text-to-image (T2I) models have led to remarkable success in generating high-quality images from textual prompts. However, ensuring accurate alignment between the text and the generated image remains a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Jia Jun Cheng Xian , Muchen Li , Haotian Yang , Xin Tao , Pengfei Wan , Leonid Sigal , Renjie Liao

In this study, we aim to enhance the capabilities of diffusion-based text-to-image (T2I) generation models by integrating diverse modalities beyond textual descriptions within a unified framework. To this end, we categorize widely used…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Sungnyun Kim , Junsoo Lee , Kibeom Hong , Daesik Kim , Namhyuk Ahn

Exploration is crucial in the design process and is known for its essential role in fostering creativity and enhancing design outcomes. Within design teams, exploration evolves into co-exploration, a collaborative and dynamic practice that…

Human-Computer Interaction · Computer Science 2025-10-03 Xinhui Ye , Joep Frens , Jun Hu

Creative coding requires continuous translation between evolving concepts and computational artifacts, making reflection essential yet difficult to sustain. Creators often struggle to manage ambiguous intentions, emergent outputs, and…

Human-Computer Interaction · Computer Science 2026-01-27 Anqi Wang , Zhengyi Li , Lan Luo , Xin Tong , Pan Hui

Explanatory images play a pivotal role in accessible and easy-to-read (E2R) texts. However, the images available in online databases are not tailored toward the respective texts, and the creation of customized images is expensive. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-10-07 Miriam Anschütz , Tringa Sylaj , Georg Groh

Text-to-image models such as stable diffusion have opened a plethora of opportunities for generating art. Recent literature has surveyed the use of text-to-image models for enhancing the work of many creative artists. Many e-commerce…

Human-Computer Interaction · Computer Science 2024-03-12 Shanu Vashishtha , Abhinav Prakash , Lalitesh Morishetti , Kaushiki Nag , Yokila Arora , Sushant Kumar , Kannan Achan

We investigate the extent to which contemporary Large Language Models (LLMs) can engage in exploration, a core capability in reinforcement learning and decision making. We focus on native performance of existing LLMs, without training…

Machine Learning · Computer Science 2024-10-30 Akshay Krishnamurthy , Keegan Harris , Dylan J. Foster , Cyril Zhang , Aleksandrs Slivkins

The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated strong power of learning complex structures and meaningful semantics. However, relying solely on text prompts cannot fully take advantage of the…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Chong Mou , Xintao Wang , Liangbin Xie , Yanze Wu , Jian Zhang , Zhongang Qi , Ying Shan , Xiaohu Qie

Generative text-to-image (T2I) models are known for their risks related such as bias, offense, and misinformation. Current AI auditing methods face challenges in scalability and thoroughness, and it is even more challenging to enable…

Human-Computer Interaction · Computer Science 2025-03-17 Yanwei Huang , Wesley Hanwen Deng , Sijia Xiao , Motahhare Eslami , Jason I. Hong , Adam Perer

Recent advancements in text-to-image (T2I) generation have enabled models to produce high-quality images from textual descriptions. However, these models often struggle with complex instructions involving multiple objects, attributes, and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Yucheng Zhou , Jiahao Yuan , Qianning Wang

Instruction-tuning can be substantially optimized through enhanced diversity, resulting in models capable of handling a broader spectrum of tasks. However, existing data employed for such tuning often exhibit an inadequate coverage of…

Computation and Language · Computer Science 2023-10-25 Fanqi Wan , Xinting Huang , Tao Yang , Xiaojun Quan , Wei Bi , Shuming Shi
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