What Really Works for Universal Multimodal Embeddings? A Controlled Study of Contrastive Training Strategies

Contrastive learning has become the standard paradigm for multimodal representation learning, aligning semantically matched pairs while separating mismatched ones in a shared embedding space. Although various contrastive training strategies have been proposed across negative selection, batch constru