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Related Questions
- How do NLP pipelines handle out-of-vocabulary (OOV) words in text classification tasks?
- What techniques are used to handle unseen words in word embeddings for text classification tasks?
- Can you explain how word embeddings are updated or adapted for unseen words in NLP pipelines?
- How do NLP pipelines handle the issue of word embeddings for rare or infrequent words in text classification tasks?
- What is the impact of unseen words on the performance of text classification models in NLP pipelines?
- Can you describe the process of training word embeddings for unseen words in NLP pipelines?
- How do NLP pipelines handle the trade-off between vocabulary size and word embedding quality for unseen words in text classification tasks?
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