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Related Questions
- How does continuous bag-of-words (CBOW) model work in dynamic word embeddings?
- What are the key differences between CBOW and skip-gram models in word embeddings?
- Can you explain the role of negative sampling in CBOW and its impact on word embedding quality?
- How does CBOW handle out-of-vocabulary words and rare words in text data?
- What are the advantages of using CBOW over other word embedding techniques, such as word2vec?
- Can you provide an example of how CBOW is used in a real-world application, such as text classification or language modeling?
- How does CBOW handle polysemy and homographs in word embeddings, and what are the implications for downstream NLP tasks?
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