Year: 2026
Type: preprint
Abstract: Real user studies are important for understanding how people interact with systems under test or already deployed. In practice, however, they are often costly, time-consuming, and difficult to scale. To address these challenges, we introduce PersonaEval, a persona-based user simulation framework that approximates real-user behavior across diverse interactive settings. PersonaEval connects simulated users drawn from existing persona datasets to task-specific application interfaces and collects the interaction trajectories and outcomes. PersonaEval provides a plug-and-play evaluation workflow in which the application being evaluated can be easily changed. In this demo, we present PersonaEval on three forms of interactive applications: surveys, chatbots, and web applications. Together, these examples show that PersonaEval can support repeatable, parallelizable, and scalable evaluation across different interaction settings, while producing user-oriented feedback and task-specific behavior.
Source: arXiv (Cornell University)
Authors: Liu, Yifan Simon, Wen, Qianfeng, Fan, Yilan, Huang, Shirley, Gao, Ruoqi, Hou, Jianheng, Mohsin, Muhammad Ahmed, Di, Zonglin, Joshi, Brihi, Tan, Xincheng, Lu, Yucheng, Liu, Xiaoyi, Liu, Heming, Xing, Hanwen, Min, Guanghui, Shan, Zhengyang, Nguyen, My Chiffon, Gupta, Ishan, Xiao, Yunze, Collison, Hannah, Huang, Jintao, Li, Jiatong, Jajee, Sankalp, Zhao, Yunhan, Hu, Bing, Ng, Sky, Chen, Xupeng, Lu, Binghang, Xiao, Weihang, Mohan, Aravind, Sun, Bolun, Wu, Yunshu, Xu, Yuanda, Shen, Yun, Zhang, Runyu, Deng, Zheyuan, Zhang, Zhiwei, Zhu, Qianyu, Wang, Dianzhuo, Wang, Yijun, He, Yixuan, Hao, Yuexing, Li, Xiaomin
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7203719439
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