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Related Questions
- What are the most effective data augmentation techniques for reducing hallucinations in LLMs?
- How can injecting noise and randomness into training data increase diversity and decrease hallucinations?
- What is the role of adversarial training in augmenting data to combat hallucinations in LLMs?
- Can you explain how dataset curators can create realistic and diverse data augmentations to prevent hallucinations?
- What metrics can be used to measure the effectiveness of data augmentation in reducing hallucinations?
- How do you address the trade-off between increasing diversity and degrading performance when applying data augmentation techniques?
- What are some of the key considerations when developing data augmentation strategies to target specific hallucination types?
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