New Concepts in Human-Computer Interaction Design and Application

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: closed (15 March 2025) | Viewed by 407

Special Issue Editor


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Guest Editor
School of Design, Hunan University, Changsha 410082, China
Interests: computer graphics; machine learning; artificial intelligence; human–computer interaction; intelligent design

Special Issue Information

Dear Colleagues,

With the rapid advancement of large language models, generative AI, and agents, the paradigms and applications of human–computer collaborative design are undergoing profound transformations. These technologies not only extend the boundaries of creativity and intelligence but also revolutionize the design process by integrating multimodal data, including text, images, and audio. LLMs can accurately comprehend and generate high-quality content across various contexts, while AIGC, building on learning and induction, further evolves and creates by simulating human creative thinking, thus achieving a leap from perception and understanding to generation and creation. Agents, with their advanced features such as context-aware memory, multi-step planning, and strategic tool usage, further augment the capabilities of LLMs. AI is no longer merely a tool; it acts as an extension of human intent, actively engaging in design and production practices. These technological advancements are ushering in a new era in the design field, characterized by increasingly diverse and intelligent design paradigms and application trends.

This Special Issue focuses on the transformative impact of these technologies on human–computer collaborative design, exploring emerging design paradigms and application trends. We invite papers that explore new design paradigms and applications, with a particular focus on the practical applications of large language models, multimodal generation, and multi-agent systems in design, and how these technologies integrate with human creativity to drive innovation in design processes, tools, and user experiences.

Prof. Dr. Yi Xiao
Guest Editor

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Keywords

  • large language models
  • iagents
  • generative AI
  • human–computer interaction
  • multimodal content generation
  • design paradigms
  • collaborative design

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Published Papers (1 paper)

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Research

23 pages, 34833 KiB  
Article
AI-Assisted Design: Intelligent Generation of Dong Paper-Cut Patterns
by Yi Xiao, Xuefei Lin, Tie Ji, Jinhao Qiao, Bowen Ma and Hao Gong
Electronics 2025, 14(9), 1804; https://doi.org/10.3390/electronics14091804 - 28 Apr 2025
Viewed by 77
Abstract
Intelligent generation technology has been widely applied in the field of design, serving as an essential tool for many designers. This study focuses on the paper-cut patterns of Qin Naishiqing, an inheritor of Dong paper-cutting intangible cultural heritage, and explores the AI-assisted generation [...] Read more.
Intelligent generation technology has been widely applied in the field of design, serving as an essential tool for many designers. This study focuses on the paper-cut patterns of Qin Naishiqing, an inheritor of Dong paper-cutting intangible cultural heritage, and explores the AI-assisted generation of Dong paper-cut patterns under designer–AI collaborative control. It proposes a new role for designers in human–AI collaborative design—the “designer-in-the-loop” model. From the perspective of dataset annotation, designers conduct visual feature analysis, Shape Factor Extraction, and Semantic Factor extraction of paper-cut patterns, actively participating in dataset construction, annotation, and collaborative control methods, including using localized LoRA for detail enhancement and creating controllable collaborative modes through contour lines and structural lines, evaluation of generated results, and iterative optimization. The experimental results demonstrate that the intelligent generation approach under the “designer-in-the-loop” model, combined with designer–AI controllable collaboration, effectively enhances the generation of specific-style Dong paper-cut patterns with limited sample data. This study provides new insights and practical methodologies for the intelligent generation of other stylistic patterns. Full article
(This article belongs to the Special Issue New Concepts in Human-Computer Interaction Design and Application)
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