GenFaceUI: Meta-Design of Generative Personalized Facial Expression Interfaces for Intelligent Agents
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866912897905459200 |
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| author | Ge, Yate Tian, Lin Dai, Yi Pan, Shuhan Zhang, Yiwen Wang, Qi Guo, Weiwei Sun, Xiaohua |
| author_facet | Ge, Yate Tian, Lin Dai, Yi Pan, Shuhan Zhang, Yiwen Wang, Qi Guo, Weiwei Sun, Xiaohua |
| contents | This work investigates generative facial expression interfaces for intelligent agents from a meta-design perspective. We propose the Generative Personalized Facial Expression Interface (GPFEI) framework, which organizes rule-bounded spaces, character identity, and context--expression mapping to address challenges of control, coherence, and alignment in run-time facial expression generation. To operationalize this framework, we developed GenFaceUI, a proof-of-concept tool that enables designers to create templates, apply semantic tags, define rules, and iteratively test outcomes. We evaluated the tool through a qualitative study with twelve designers. The results show perceived gains in controllability and consistency, while revealing needs for structured visual mechanisms and lightweight explanations. These findings provide a conceptual framework, a proof-of-concept tool, and empirical insights that highlight both opportunities and challenges for advancing generative facial expression interfaces within a broader meta-design paradigm. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_11055 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | GenFaceUI: Meta-Design of Generative Personalized Facial Expression Interfaces for Intelligent Agents Ge, Yate Tian, Lin Dai, Yi Pan, Shuhan Zhang, Yiwen Wang, Qi Guo, Weiwei Sun, Xiaohua Human-Computer Interaction H.5.2; I.2.0 This work investigates generative facial expression interfaces for intelligent agents from a meta-design perspective. We propose the Generative Personalized Facial Expression Interface (GPFEI) framework, which organizes rule-bounded spaces, character identity, and context--expression mapping to address challenges of control, coherence, and alignment in run-time facial expression generation. To operationalize this framework, we developed GenFaceUI, a proof-of-concept tool that enables designers to create templates, apply semantic tags, define rules, and iteratively test outcomes. We evaluated the tool through a qualitative study with twelve designers. The results show perceived gains in controllability and consistency, while revealing needs for structured visual mechanisms and lightweight explanations. These findings provide a conceptual framework, a proof-of-concept tool, and empirical insights that highlight both opportunities and challenges for advancing generative facial expression interfaces within a broader meta-design paradigm. |
| title | GenFaceUI: Meta-Design of Generative Personalized Facial Expression Interfaces for Intelligent Agents |
| topic | Human-Computer Interaction H.5.2; I.2.0 |
| url | https://arxiv.org/abs/2602.11055 |