Evaluating Scene-based In-Situ Item Labeling for Immersive Conversational Recommendation
The growing ubiquity of Extended Reality (XR) is driving Conversational Recommendation Systems (CRS) toward visually immersive experiences. We formalize this paradigm as Immersive CRS (ICRS), where recommended items are highlighted directly in the user's scene-based visual environment and augmented with in-situ labels. While item recommendation has been widely studied, the problem of how to select and evaluate which information to present as immersive labels remains an open problem. To this end, we introduce a principled categorization of information needs into explicit intent satisfaction and proactive information needs and use these to define novel evaluation metrics for item label sele...
| Authors | Jiazhou Liang, Yifan Simon Liu, David Guo et al. |
|---|---|
| Primary category | cs.IR |
| Published | 6 April 2026 |
| Last updated at source | 24 June 2026 |
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