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Deep learning offers transformative potential in medical imaging, yet its clinical adoption is frequently hampered by challenges such as data scarcity, distribution shifts, and the need for robust task generalization. Prompt-based…

Image and Video Processing · Electrical Eng. & Systems 2025-07-03 Hao Yang , Xinlong Liang , Zhang Li , Yue Sun , Zheyu Hu , Xinghe Xie , Behdad Dashtbozorg , Jincheng Huang , Shiwei Zhu , Luyi Han , Jiong Zhang , Shanshan Wang , Ritse Mann , Qifeng Yu , Tao Tan

Recent technological advances popularized the use of image generation among the general public. Crafting effective prompts can, however, be difficult for novice users. To tackle this challenge, we developed PromptMap, a new interaction…

Human-Computer Interaction · Computer Science 2025-04-04 Krzysztof Adamkiewicz , Paweł W. Woźniak , Julia Dominiak , Andrzej Romanowski , Jakob Karolus , Stanislav Frolov

To support junior and senior architects, I propose developing a new architecture creation method that leverages LLMs' evolving capabilities to support the architect. This method involves the architect's close collaboration with LLM-fueled…

Software Engineering · Computer Science 2025-05-27 Tobias Eisenreich

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

This study explores the potential of generative artificial intelligence (AI) models, specifically OpenAI's generative pre-trained transformer (GPT) series, when integrated with building information modeling (BIM) tools as an interactive…

Artificial Intelligence · Computer Science 2024-10-21 Suhyung Jang , Ghang Lee

With their remarkable ability to generate code, large language models (LLMs) are a transformative technology for computing education practice. They have created an urgent need for educators to rethink pedagogical approaches and teaching…

Human-Computer Interaction · Computer Science 2023-08-01 Paul Denny , Juho Leinonen , James Prather , Andrew Luxton-Reilly , Thezyrie Amarouche , Brett A. Becker , Brent N. Reeves

Large Language Models (LLMs) have the potential to revolutionize automated traceability by overcoming the challenges faced by previous methods and introducing new possibilities. However, the optimal utilization of LLMs for automated…

Software Engineering · Computer Science 2023-08-02 Alberto D. Rodriguez , Katherine R. Dearstyne , Jane Cleland-Huang

Human language is one of the most expressive tools for conveying intent, yet most artificial or biological systems lack mechanisms to interpret or respond meaningfully to it. Bridging this gap could enable more natural forms of control over…

Artificial Intelligence · Computer Science 2025-09-16 Nam H. Le , Patrick Erickson , Yanbo Zhang , Michael Levin , Josh Bongard

Text-based prompting remains the predominant interaction paradigm in generative AI, yet it often introduces friction for novice users such as small business owners (SBOs), who struggle to articulate creative goals in domain-specific…

Human-Computer Interaction · Computer Science 2025-04-23 Nimisha Karnatak , Adrien Baranes , Rob Marchant , Huinan Zeng , Tríona Butler , Kristen Olson

Large Language Models (LLMs) are nowadays extensively used for various types of software engineering tasks, primarily code generation. Previous research has shown how suitable prompt engineering could help developers in improving their code…

Mechanical metamaterials utilize intricate architectural designs to achieve advanced properties beyond those of their bulk counterparts. Existing metamaterial designs often rely on design inspirations and extensive experimental and…

Design inspiration is crucial for establishing the direction of a design as well as evoking feelings and conveying meanings during the conceptual design process. Many practice designers use text-based searches on platforms like Pinterest to…

Human-Computer Interaction · Computer Science 2024-07-18 Ye Wang , Nicole B. Damen , Thomas Gale , Voho Seo , Hooman Shayani

Despite recent progress in text-to-image (T2I) generation, existing models often struggle to faithfully capture user intentions from short and under-specified prompts. While prior work has attempted to enhance prompts using large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Mingrui Wu , Lu Wang , Pu Zhao , Fangkai Yang , Jianjin Zhang , Jianfeng Liu , Yuefeng Zhan , Weihao Han , Hao Sun , Jiayi Ji , Xiaoshuai Sun , Qingwei Lin , Weiwei Deng , Dongmei Zhang , Feng Sun , Qi Zhang , Rongrong Ji

Generative AI, i.e., the group of technologies that automatically generate visual or written content based on text prompts, has undergone a leap in complexity and become widely available within just a few years. Such technologies…

Human-Computer Interaction · Computer Science 2023-03-17 Nanna Inie , Jeanette Falk , Steven Tanimoto

Prompt engineering is a challenging yet crucial task for optimizing the performance of large language models on customized tasks. It requires complex reasoning to examine the model's errors, hypothesize what is missing or misleading in the…

Computation and Language · Computer Science 2024-07-04 Qinyuan Ye , Maxamed Axmed , Reid Pryzant , Fereshte Khani

"Prompt Engineering for Students of Medicine and Their Teachers" brings the principles of prompt engineering for large language models such as ChatGPT and Google Bard to medical education. This book contains a comprehensive guide to prompt…

Human-Computer Interaction · Computer Science 2023-08-24 Thomas F. Heston

While generative AI enables high-fidelity UI generation from text prompts, users struggle to articulate design intent and evaluate or refine results-creating gulfs of execution and evaluation. To understand the information needed for UI…

Human-Computer Interaction · Computer Science 2026-02-10 Seokhyeon Park , Soohyun Lee , Eugene Choi , Hyunwoo Kim , Minkyu Kweon , Yumin Song , Jinwook Seo

Due to their architecture and vast pre-training data, large language models (LLMs) demonstrate strong text classification performance. However, LLM output - here, the category assigned to a text - depends heavily on the wording of the…

Computation and Language · Computer Science 2025-12-04 Kylie L. Anglin , Stephanie Milan , Brittney Hernandez , Claudia Ventura

Environment designers in the entertainment industry create imaginative 2D and 3D scenes for games, films, and television, requiring both fine-grained control of specific details and consistent global coherence. Designers have increasingly…

Human-Computer Interaction · Computer Science 2025-09-03 Wen-Fan Wang , Ting-Ying Lee , Chien-Ting Lu , Che-Wei Hsu , Nil Ponsa Campanyà , Yu Chen , Mike Y. Chen , Bing-Yu Chen

Designing effective software architectures is a complex, iterative process that traditionally relies on expert judgment. This paper proposes an approach for Large Language Model (LLM)-assisted software architecture design using the…

Software Engineering · Computer Science 2025-07-01 Humberto Cervantes , Rick Kazman , Yuanfang Cai
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