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Related Questions
- How does limited training data impact a large language model's ability to generalize to novel domains?
- Can a model's performance degrade when it encounters unfamiliar topics or genres not present in its training data?
- What are some strategies to mitigate the effects of limited training data on a model's adaptability?
- How might a model's inability to adapt to new domains impact its overall performance and usefulness?
- What role does domain adaptation play in improving a model's ability to handle out-of-distribution data?
- Can you explain the concept of 'cognitive bias' in the context of a model's training data and its effects on adaptability?
- How might a model's performance be affected by the quality and diversity of its training data?
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