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Related Questions
- What techniques does the model use to handle out-of-vocabulary (OOV) words in language translation tasks?
- How does the model deal with unknown words during text summarization tasks?
- Can the model learn to infer the meaning of OOV words from context or additional training data?
- What is the impact of OOV words on the overall performance of the model in language translation and text summarization tasks?
- Are there any techniques to improve the model's handling of OOV words, such as subword modeling or character-level modeling?
- Can the model learn to replace OOV words with synonymous words or phrases to maintain the overall meaning of the text?
- How does the model's handling of OOV words affect its ability to generalize to new, unseen data in language translation and text summarization tasks?
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