SOURCE-LINKED INTELLIGENCE
Pseudo-Label Augmentation for Affect Sensing in Small Collaborative Groups
Physiological affect sensing in naturalistic group interaction is often limited by sparse labels rather than sensor data: wearable devices produce many time windows, while self-reports are collected only a few times per session. Using GroupAffect-4, a four-person collaborative dataset with wearable physiology, eye tracking, Big Five personality, and post-task VAD labels, we study pseudo-label augmentation for affect sensing under sparse supervision. We compare no augmentation, Gaussian Process pseudo-labelling, personality-aware trust weighting, and joint personality-plus-confidence weighting
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-13T17:39:53.000Z
First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.