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Related Questions
- How do data augmentation techniques like back-translation and paraphrasing affect the performance of LLMs on in-distribution data?
- Can you explain the concept of out-of-distribution data and how LLMs can be vulnerable to it?
- What are some common data augmentation techniques used to improve the robustness of LLMs?
- How does back-translation work and what are its benefits in improving LLM robustness?
- What is the difference between paraphrasing and back-translation in the context of LLM robustness?
- Can you provide examples of how data augmentation can be used to increase the robustness of LLMs to out-of-distribution data?
- What are some potential limitations and challenges of using data augmentation techniques to improve LLM robustness?
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