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Related Questions
- How do word2vec and GloVe handle out-of-vocabulary words in a language model?
- Can you explain the difference in performance of language models using word2vec and GloVe on rare words?
- What techniques can be used to improve the performance of a language model on rare words?
- How do the dimensions of word embeddings in word2vec and GloVe affect the performance on rare words?
- Can you discuss the impact of pre-training a language model on a large corpus versus a smaller corpus on rare word performance?
- How do different word embedding techniques, such as fastText and word2vec, compare in handling rare words?
- What are some common pitfalls to avoid when using word embeddings for rare words in a language model?
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