AI 前沿资讯：Why do the output layer weight…

Im trying to understand the intuition behind Word2Vec training using a neural network. In Word2Vec (CBOW or Skip-gram), we often hear that the weight matrices learned during training contain the vector representations (embeddings) of words. However, I dont understand why the weights of the hidden-to-output layer (or output weight matrix) end up representing semantic features of words. Why do these…

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