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Related Questions
- How do subword embeddings improve the accuracy of language models when dealing with rare or out-of-vocabulary words?
- Can you explain the process of subwordization and how it enables language models to handle words that are not present in the training data?
- How do subword embeddings compare to traditional word embeddings in terms of representing rare or unknown words?
- What are the key benefits of using subword embeddings in natural language processing tasks, especially for languages with a high degree of out-of-vocabulary words?
- Can subword embeddings be used in conjunction with word embeddings to improve the overall performance of a language model?
- How do subword embeddings handle polysemous words, where a single word has multiple meanings?
- What are some common use cases for subword embeddings in real-world applications, such as text classification or machine translation?
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