cross-modal-prediction

LeVLJEPA is the first fully non-contrastive end-to-end vision-language pretraining method, achieving competitive performance with CLIP and SigLIP without negatives, temperature, or momentum encoder. It learns via cross-modal prediction with stop-gradient targets and per-modality distributional regularization, providing stronger dense semantic features for downstream tasks like VLM backbones and semantic segmentation.