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Related Questions
- How do large language models handle out-of-vocabulary words during training and inference?
- What are the common techniques used to mitigate the impact of out-of-vocabulary words on model performance?
- Can you explain the concept of subwording and its role in handling out-of-vocabulary words in large language models?
- What is the effect of out-of-vocabulary words on model accuracy and how can it be measured?
- How do different model architectures, such as transformer and recurrent neural networks, handle out-of-vocabulary words?
- What are the potential consequences of ignoring out-of-vocabulary words in large language models, such as reduced generalizability and interpretability?
- Can you discuss the trade-offs between model size, complexity, and the ability to handle out-of-vocabulary words in large language models?
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