Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling
Recent research introduces a framework for enhancing virtual agents' emotional interactions. The Cross-Temporal Emotion Modeling (CTEM) aims to create more natural and companionable experiences by linking past behaviors to current emotional states. A study of a companion agent named Auri demonstrated improvements in perceived naturalness and emotional coherence over a 21-day period.
- ▪The study presents Cross-Temporal Emotion Modeling (CTEM) to improve virtual agents' emotional interactions.
- ▪CTEM connects long-term behavioral history with moment-to-moment emotional expressions.
- ▪Auri, the companion agent developed using CTEM, showed significant improvements in user experience during a 21-day study.
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Computer Science > Human-Computer Interaction arXiv:2605.15812 (cs) [Submitted on 15 May 2026] Title:Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling Authors:Feier Qin, Xiao Li, Yi Zheng, Haibin Huang, Hanyao Wang, Xiaoyu Wang, Yan Lu, Yuan Zhang View a PDF of the paper titled Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling, by Feier Qin and 7 other authors View PDF HTML (experimental) Abstract:Recent advances in foundation models have enabled conversational agents that aim for sustained companionship rather than mere task completion. Yet most still remain unable to support natural, long-term companion-like interactions, resulting in experiences that feel episodic and inauthentic.
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