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Diffusion models equipped with language models demonstrate excellent controllability in image generation tasks, allowing image processing to adhere to human instructions. However, the lack of diverse instruction-following data hampers the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Yongsheng Yu , Ziyun Zeng , Hang Hua , Jianlong Fu , Jiebo Luo

Text-guided image editing finds applications in various creative and practical fields. While recent studies in image generation have advanced the field, they often struggle with the dual challenges of coherent image transformation and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Rumeysa Bodur , Binod Bhattarai , Tae-Kyun Kim

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

Generative AI, such as image generation models and large language models, stands to provide tremendous value to end-user programmers in creative and knowledge workflows. Current research methods struggle to engage end-users in a realistic…

Human-Computer Interaction · Computer Science 2023-12-29 Advait Sarkar , Ian Drosos , Rob Deline , Andrew D. Gordon , Carina Negreanu , Sean Rintel , Jack Williams , Benjamin Zorn

Prompt engineering is a technique that involves augmenting a large pre-trained model with task-specific hints, known as prompts, to adapt the model to new tasks. Prompts can be created manually as natural language instructions or generated…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Jindong Gu , Zhen Han , Shuo Chen , Ahmad Beirami , Bailan He , Gengyuan Zhang , Ruotong Liao , Yao Qin , Volker Tresp , Philip Torr

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

Text-to-image generation has recently emerged as a viable alternative to text-to-image retrieval, driven by the visually impressive results of generative diffusion models. Although query performance prediction is an active research topic in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Eduard Poesina , Adriana Valentina Costache , Adrian-Gabriel Chifu , Josiane Mothe , Radu Tudor Ionescu

Prompting is central to interaction with AI systems, yet many users struggle to explore alternative directions, articulate creative intent, or understand how variations in prompts shape model outputs. We introduce prompt recommender systems…

Human-Computer Interaction · Computer Science 2026-01-23 Jason Kim , Maria Teleki , James Caverlee

Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models often struggle with simple or underspecified prompts, leading to suboptimal image-text alignment, aesthetics, and quality. We propose a…

Computation and Language · Computer Science 2025-10-16 Ruibo Chen , Jiacheng Pan , Heng Huang , Zhenheng Yang

Using a text description as prompt to guide the generation of text or images (e.g., GPT-3 or DALLE-2) has drawn wide attention recently. Beyond text and image generation, in this work, we explore the possibility of utilizing text…

Audio and Speech Processing · Electrical Eng. & Systems 2022-11-23 Zhifang Guo , Yichong Leng , Yihan Wu , Sheng Zhao , Xu Tan

Personalized image generation via text prompts has great potential to improve daily life and professional work by facilitating the creation of customized visual content. The aim of image personalization is to create images based on a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Mingxiao Li , Tingyu Qu , Tinne Tuytelaars , Marie-Francine Moens

State-of-the-art visual generative AI tools hold immense potential to assist users in the early ideation stages of creative tasks -- offering the ability to generate (rather than search for) novel and unprecedented (instead of existing)…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Evans Xu Han , Alice Qian Zhang , Haiyi Zhu , Hong Shen , Paul Pu Liang , Jane Hsieh

Large language models (LLMs) have shown remarkable success across a wide range of natural language generation tasks, where proper prompt designs make great impacts. While existing prompting methods are normally restricted to providing…

Computation and Language · Computer Science 2023-06-01 Bei Li , Rui Wang , Junliang Guo , Kaitao Song , Xu Tan , Hany Hassan , Arul Menezes , Tong Xiao , Jiang Bian , JingBo Zhu

Text-to-image generative models have recently exploded in popularity and accessibility. Yet so far, use of these models in creative tasks that bridge the 2D digital world and the creation of physical artefacts has been understudied. We…

Artificial Intelligence · Computer Science 2023-02-02 Amy Smith , Hope Schroeder , Ziv Epstein , Michael Cook , Simon Colton , Andrew Lippman

Text-to-image diffusion models have achieved remarkable performance in image synthesis, while the text interface does not always provide fine-grained control over certain image factors. For instance, changing a single token in the text can…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Chen Wu , Fernando De la Torre

Large language models can perform various reasoning tasks by using chain-of-thought prompting, which guides them to find answers through step-by-step demonstrations. However, the quality of the prompts depends on the demonstrations given to…

Computation and Language · Computer Science 2023-02-02 Zhihong Shao , Yeyun Gong , Yelong Shen , Minlie Huang , Nan Duan , Weizhu Chen

Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements for storytelling. Existing approaches to this problem…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Tao Liu , Kai Wang , Senmao Li , Joost van de Weijer , Fahad Shahbaz Khan , Shiqi Yang , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Plain text has become a prevalent interface for text-to-image synthesis. However, its limited customization options hinder users from accurately describing desired outputs. For example, plain text makes it hard to specify continuous…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Songwei Ge , Taesung Park , Jun-Yan Zhu , Jia-Bin Huang

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

Personalized text-to-image generation has attracted unprecedented attention in the recent few years due to its unique capability of generating highly-personalized images via using the input concept dataset and novel textual prompt. However,…

Artificial Intelligence · Computer Science 2024-07-02 Shian Du , Xiaotian Cheng , Qi Qian , Henglu Wei , Yi Xu , Xiangyang Ji