LingBot-Vision: masked boundary modeling for self-supervised pretraining (0.296 NYUv2 linear-probe RMSE at 1.1B vs 0.309 for DINOv3-7B, trails on ImageNet); weights in 4 sizes[R]

The idea: instead of masking random patches and hoping boundary structure emerges, the teacher predicts a dense boundary field online and the boundary-bearing tokens are forced into the student's mask, so the student has to reconstruct exactly the regions that can't be inferred by copying context. T