2 papers
cs.CV2026
TeMo: Temperature Modulation for Multimodal Contrastive Learning
Dhimitrios Duka, Bernt Schiele, Hilde Kuehne +1
Contrastive learning approaches achieve strong performance by training models to bring similar samples closer while pushing dissimilar samples apart. A crucial component of contras…
cs.CV2026
MM-TS: Multi-Modal Temperature and Margin Schedules for Contrastive Learning with Long-Tail Data
Siarhei Sheludzko, Dhimitrios Duka, Bernt Schiele +2
Contrastive learning has become a fundamental approach in both uni-modal and multi-modal frameworks. This learning paradigm pulls positive pairs of samples closer while pushing neg…