The training loss is the distance between the predictor’s output and the target encoder’s representation, computed after both are normalized to unit length (L2 normalization). Minimizing this normalized MSE is equivalent to maximizing the cosine similarity between the two representations. The model learns to match the direction of embeddings (their semantic meaning), not their magnitude.
The Apps Running Quietly in the Background。关于这个话题，黑料提供了深入分析
，详情可参考手游
В Иране заявили о ракетном ударе по разбившемуся американскому самолету02:12
ВСУ ударили по Брянску британскими ракетами. Под обстрел попал завод, есть жертвы19:57，详情可参考今日热点
— Switch between modified files: C-x C-g lets you