Yeye Li

dblp:390/3496 · DBLP profile ↗
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4ranked-venue papers
1as first author
4since 2021 · last 2025
0009-0000-9087-4403ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 4 · 1 first-author · 4 since 2021
YearPublicationVenuePosition
2025 Customizable AI for Depression Care: Improving the User Experience of Large Language Model-Driven Chatbots
Yi Li 0075, Xuanxuan Ding, Yeye Li, Nan Ma 0003
Conference on Designing Interactive Systems4
2025 Evaluating User Perception of Wearable ECG Devices: Facilitating and Inhibiting Factors Moderated by Health Consciousness
abstract
This study aims to investigate the key factors affecting the use and interaction of wearable ECG devices from the user's perception. A conceptual model is proposed that combines an expectation-confirmation model with facilitating and inhibiting factors. Besides, health consciousness is set as a moderating variable. A quantitative study is conducted with users who have real-world experience with wearable ECG devices, the findings suggest that the perceived availability and compatibility of wearable ECG devices have a positive effect on confirmation and satisfaction. Technical anxiety and transition costs negatively affect satisfaction but have no impact on confirmation. Health consciousness can mitigate the negative effects of technological anxiety and transition costs while positively moderating the impact of perceived compatibility on satisfaction. The study recommendations focus on optimizing product reliability and real-time visual feedback, while ensuring multi-scenario compatibility and adopting differentiated design strategies. Additionally, incorporating health education and reward mechanisms is suggested.
Nan Ma 0003, Yi Li 0075, Yeye Li, Lin Guo 0014
Int. J. Hum. Comput. Interact.3
2025 Digital Civic Engagement in China: Using 'Micro Advice' Platform to Improve People's Livelihood
abstract
Micro Advice is a mobile platform for democratic governance in China, allowing access to voice social issues and advice to the government with the aim of improving people's livelihood. However, due to the lack of first-hand experience, the current understanding of how end-users utilize Micro Advice to participate in democratic governance is incomplete. We interviewed 12 users to understand their practices and challenges in using the platform. Specifically, we illustrate the user's experience, introduce what difficulties they encountered, and how they strategically use the platform to improve people's livelihood. We also investigate the socio-technical aspects of Micro Advice within the Chinese political context, discussing how to accept and utilize Micro Advice in China's social environment, and develop technological solutions adapted to these backgrounds. Finally, we propose some design implications for civic technology participation platforms. Micro Advice provides a novel, open, and real-time channel for civic engagement, showcasing the practical effects and impact of digitized civic engagement in China. It offers researchers a new perspective for expressing and addressing societal issues. We believe that the innovation and insights of Micro Advice can extend to other types of digitized civic engagement initiatives. We will continue to explore the interactive processes between the government and the public, along with innovative technological approaches.
Yeye Li, Hanhui Deng, Nan Ma 0003, Xin Tong 0004, Mingming Fan 0001, Da-Fang Zhang 0001, Yi Li 0075, Di Wu 0002
Proc. ACM Hum. Comput. Interact.1
2024 StyleWe: Towards Style Fusion in Generative Fashion Design with Efficient Federated AI
abstract
Collaboration can amalgamate diverse ideas, styles, and visual elements, fostering creativity and innovation among different designers. In collaborative design, sketches play a pivotal role as a means of expressing design creativity. However, designers often tend to not openly share these meticulously crafted sketches. This phenomenon of data island in the design area hinders its digital transformation under the third wave of AI. In this paper, we introduce a Federated Generative Artificial Intelligence Clothing system, namely StyleWe, employing federated learning to aid in sketch design. StyleWe is committed to establishing an ecosystem wherein designers can exchange sketch styles among themselves. Through StyleWe, designers can generate sketches that incorporate various designers' styles from their peers, drawing inspiration from collaboration without the need for data disclosure or upload. Extensive performance evaluations and user studies indicate that our StyleWe system can produce multi-styled sketches of comparable quality to human-designed ones while significantly enhancing efficiency compared to hand-drawn sketches.
Di Wu 0002, Mingzhu Wu, Yeye Li, Jianan Jiang, Xinglin Li, Hanhui Deng, Can Liu 0003, Yi Li 0075
Proc. ACM Hum. Comput. Interact.3