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Related Questions
- What are out-of-vocabulary (OOV) words and how do they affect the performance of language models in real-world scenarios?
- Can you explain the impact of OOV words on the robustness of language models in tasks such as sentiment analysis and text classification?
- How do language models handle OOV words, and what are the consequences of not handling them properly?
- What are some strategies for mitigating the effects of OOV words on language model performance in real-world applications?
- Can you discuss the relationship between OOV words and model interpretability, and how it affects the trustworthiness of language models?
- How do OOV words impact the generalizability of language models to new, unseen data, and what are the implications for model deployment?
- What are some real-world examples of OOV words causing issues in language model performance, and how were they addressed?
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