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Related Questions
- Can data augmentation techniques such as back-translation and paraphrasing be used to increase the robustness of LLMs to out-of-distribution data?
- How does data augmentation impact the performance of LLMs on handling unseen or novel input data?
- What are some common data augmentation techniques used to improve the robustness of LLMs to out-of-distribution data?
- Can data augmentation be used to improve the generalizability of LLMs to different languages or domains?
- How does data augmentation affect the interpretability of LLMs, particularly when dealing with out-of-distribution data?
- Can data augmentation be used to mitigate the effects of adversarial attacks on LLMs?
- What are the potential trade-offs between data augmentation and overfitting in LLMs, especially when dealing with out-of-distribution data?
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