A JEPA-Inspired Span-Masked Framework for Language Representation Learning: Revisiting Cosine Similarity and VICReg Regularization
Joint-Embedding Predictive Architectures (JEPAs) have recently emerged as a promising paradigm for self-supervised representation learning by predicting latent embeddings from partial observations rather than reconstructing raw inputs. Although JEPA has demonstrated considerable success in computer vision and large-sca...