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Related Questions
- How do out-of-vocabulary (OOV) words affect the performance of large language models (LLMs)?
- What are some common techniques used to handle OOV words in LLMs, and what are their limitations?
- Can you explain the concept of subword modeling and its role in reducing OOV words in LLMs?
- How does the choice of vocabulary size impact OOV word performance in LLMs, and what are the trade-offs?
- What is the impact of OOV words on the interpretability of LLMs, and how can it be addressed?
- Can you discuss the relationship between OOV words and the need for additional training data in LLMs?
- What are some recent advancements in LLMs that address the issue of OOV words, and how do they work?
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