AI RESEARCH
How (Mis)calibrated is Your Federated CLIP and What To Do About It?
arXiv CS.CV
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ArXi:2512.04305v2 Announce Type: replace While vision-language models like CLIP have been extensively studied, their calibration, crucial for reliable predictions, has received limited attention. Although a few prior works have examined CLIP calibration in offline settings, the impact of fine-tuning CLIP in a federated learning (FL) setup remains unexplored. In this work, we investigate how FL affects CLIP calibration and propose strategies to improve reliability in this distributed setting.