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Related Questions
- How do the rare word handling techniques in word2vec and GloVe affect the model's performance on out-of-vocabulary words?
- Can you explain the impact of subwording and masking on the model's ability to generalize to unseen data?
- How do the word2vec and GloVe models handle rare words, and what are the implications for their ability to generalize?
- What are the trade-offs between using subwording, masking, and other rare word handling techniques in word2vec and GloVe?
- How do the word2vec and GloVe models handle polysemy and homographs, and what impact does this have on their ability to generalize?
- Can you discuss the role of rare word handling techniques in word2vec and GloVe in relation to the model's ability to capture semantic relationships?
- What are some common pitfalls or challenges associated with rare word handling in word2vec and GloVe, and how can they be addressed?
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