Understanding Word Embeddings $1$ point possible $($graded$)$ Which of the following options is correct about word embeddings presented in the lecture. The goal of word embeddings is to increase the sparsity of the encoded input word features We would like similar words to have word embeddings that are far apart in order to minimize word sense disambiguation One way to learn word embeddings is by maximizing cosine similarity between words with related meaning. To do a good job, word embeddings have to manually encoded by a natural language domain expert unanswered