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Related Questions
- How do word embeddings, such as Word2Vec and GloVe, represent out-of-vocabulary words?
- What techniques do contextualized embeddings, like BERT and RoBERTa, use to handle out-of-vocabulary words?
- Can you explain how sparse and dense word embeddings handle out-of-vocabulary words?
- What is the impact of using different word representation techniques on out-of-vocabulary words in downstream NLP tasks?
- How do different word representation techniques balance between representing known and unknown words?
- Can you discuss the trade-offs between using a large vocabulary and handling out-of-vocabulary words with word representation techniques?
- What are some strategies for handling out-of-vocabulary words in machine translation using word representation techniques?
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