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Related Questions
- What are the common pre-training objectives used in language models, and how do they impact generalization to out-of-distribution data?
- How does the choice of pre-training objective affect the model's ability to handle unseen data, such as new domains or tasks?
- Can you explain the relationship between pre-training objective and the model's robustness to adversarial attacks or noisy inputs?
- How does the pre-training objective influence the model's capacity to generalize to tasks that are semantically similar but not identical to the pre-training tasks?
- What are the implications of using different pre-training objectives on the model's performance on out-of-distribution data?
- Can you discuss the trade-offs between pre-training objectives that prioritize fluency, accuracy, or robustness, and how they impact generalization?
- How does the pre-training objective affect the model's ability to learn abstract concepts and generalize to new, unseen situations?
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