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Related Questions
- What are some common techniques used for data augmentation in language models to improve their performance on out-of-vocabulary words?
- How does noise injection during training impact the robustness of language models to rare events?
- Can you explain the concept of 'data poisoning' and how it relates to the robustness of language models?
- What are some strategies for injecting noise into language model training data to improve their performance on rare events?
- How can data augmentation techniques be used to improve the generalizability of language models to new, unseen data?
- What are some potential drawbacks or limitations of using data augmentation and noise injection to improve language model robustness?
- Can you discuss the relationship between data augmentation, noise injection, and the concept of 'adversarial training' in language models?
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