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Related Questions
- How do out-of-vocabulary (OOV) words affect the accuracy of language models in processing natural language?
- Can you explain the ways in which OOV words can lead to errors or decreased performance in NLP tasks?
- In what ways can OOV words impact the interpretability and reliability of NLP models?
- Are there any techniques or algorithms that can help mitigate the effects of OOV words on NLP accuracy?
- How do context-dependent and context-independent learning approaches handle OOV words differently?
- Are there any datasets or metrics that can be used to evaluate the impact of OOV words on NLP tasks?
- In what ways can OOV words affect the performance of NLP models in noisy or low-resource environments?
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