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Related Questions
- How do pre-training objectives like masked language modeling and next sentence prediction impact the performance of pre-trained models on downstream tasks?
- Can you explain the role of pre-training objectives in learning generalizable representations and how this affects model performance on specific tasks?
- What are some common pre-training objectives used in large language models, and how do they influence the model's ability to perform well on tasks like question answering and text classification?
- How does the choice of pre-training objective affect the model's ability to generalize to unseen data and adapt to new tasks?
- Can you discuss the relationship between pre-training objectives and the model's ability to capture task-specific features and relationships?
- What are some potential limitations of pre-training objectives in achieving optimal performance on specific tasks, and how can these limitations be addressed?
- Can you provide examples of pre-trained models that have achieved state-of-the-art performance on specific tasks, and what pre-training objectives were used to achieve this performance?
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